
Journals >Chinese Journal of Lasers
The optical parameters of biological tissues can reflect their physiological state to a certain extent and provide an important reference basis for clinical diagnosis. Therefore, it is of great significance to measure the optical parameters of biological tissues. The commonly used methods for measuring the optical parameters of biological tissues have problems. Diffusion optical tomography has a deep imaging depth, but it relies on the depth learning algorithm of the simulated dataset, and its accuracy in practical applications is debatable. Optical coherence tomography, which has a high measurement accuracy, is only applicable to the measurement of optical parameters of shallow tissues. The direct measurement of scattering coefficients using a transmission model leads to a large error, and it cannot meet the requirements for measurement accuracy. Acousto-optic tomography (AOT) effectively combines the advantages of optical and acoustic technologies, and is expected to realize high-precision quantitative measurement of scattering coefficients of thick tissues. In this study, the feasibility of using acousto-optic signals to measure the scattering coefficients of tissues is confirmed by theory, finite element simulation, and experiment, and the advantages and disadvantages of the two types of measurement methods based on acousto-optic signals are compared.
Combining the diffuse theory of light propagation in biological tissues with the intensity modulation mechanism of acousto-optic interaction, the relationship between acousto-optic signals and the scattering coefficient is obtained. The finite element software COMSOL Multiphysics is used to simulate the acousto-optic process in the tissue to verify the correctness of the theoretical analysis results. In the AOT experiment, the peak-to-peak value and relative intensity of the acousto-optic signals are obtained by fixing the incident intensity and changing the incident intensity, respectively. Combining the relationship between acousto-optic signals and the scattering coefficient, the quantitative measurement of the scattering coefficient of the simulated tissue fluid is realized.
In the COMSOL Multiphysics simulation and AOT experiment, the peak-to-peak value of the acousto-optic signal shows a linear increasing relationship with the incident intensity (Fig. 5 and Fig. 10), and reveals an exponential decay trend with the scattering coefficient [Fig. 6(b) and Fig. 11(b)]. The relative intensity of the acousto-optic signal does not change with the change of the incident intensity (Fig. 5 and Fig. 10), and shows the same exponential decay relationship with the scattering coefficient [Fig. 6(a) and Fig. 11(a)]. The scattering coefficient of the medium is measured by the peak-to-peak value and relative intensity of the acousto-optic signal obtained by the simulation. The relative errors of the scattering coefficients obtained by both methods are within 0.5% (Fig. 7). The measurement accuracy of the former method is slightly better than that of the latter in the COMSOL Multiphysics simulation. In the AOT experiments, the maximum absolute error obtained using the relative intensity measurement method is 0.26 cm-1, the average absolute error is 0.10 cm-1, the maximum relative error is 3.88%, and the average relative error is 1.32% [Fig. 12(a)]. The maximum absolute error obtained using the peak-to-peak measurement method is 0.31 cm-1, the average absolute error is 0.12 cm-1, the maximum relative error is 3.34%, and the average relative error is 1.35% [Fig. 12(b)]. Under the same conditions, the measurement range of medium scattering coefficients using the relative intensities of acousto-optic signals is larger than that using the peak-to-peak values of acousto-optic signals [Fig. 13(a)].
In this study, the quantitative relationships between the peak-to-peak value and relative intensity of acousto-optic signals and the scattering coefficient of tissues are obtained. The peak-to-peak values of the acousto-optic signals show a linear incremental relationship with the incident intensity, but the relative intensity remains unchanged with the change in incident intensity. The relative intensity and peak-to-peak values of the acousto-optic signals show the same exponential decay trend with the increment of the scattering coefficient. The theoretical conclusions are verified through a COMSOL Multiphysics simulation and experiment. In the COMSOL Multiphysics simulation, the relative errors of the scattering coefficients based on the peak-to-peak values and relative intensities of the acousto-optic signals are both within 0.5%. In the AOT experiment, the maximum relative error of the scattering coefficient measured using the relative intensity of the acousto-optic signal is 3.88%, and the average relative error is 1.32%. The maximum relative error of the scattering coefficient measured using the peak-to-peak value of the acousto-optic signal is 3.34%, and the average relative error is 1.35%. It can be observed that the measurement accuracies of the two methods are comparable. In practice, the peak-to-peak value measurement method is fast, but the relative intensity measurement method can measure a larger range of the scattering coefficient. The above conclusions initially indicate the feasibility of high-precision quantitative measurement of scattering coefficients of biological tissues using acousto-optic signals. This is expected to provide a novel and non-invasive technical means for detecting biochemical attributes such as blood glucose, triglyceride, and total cholesterol concentrations in human blood tissues and can provide a certain reference for the clinical diagnosis of related diseases.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307101 (2025)
The relatively small fields of view of optical coherence tomography (OCT) and OCT angiography (OCTA) not only limit their clinical applications for disease diagnostics, but also lead to incorrect diagnoses. To achieve ultrawide-field OCT/OCTA imaging, two strategies are typically employed: one involves enhancing the optical design to expand the imaging field of view, which is complicated, expensive, and may introduce distortions that degrade the image quality; while the other involves performing multiple local scans with a flexible probe (such as a handheld probe), which can introduce motion artifacts. To obtain large-scale, high-quality OCT images, both flexible and stable scanning mechanisms besides high-precision image registration techniques are essential. Accordingly, in this study, a large-scale OCT imaging technique based on a 6-joint robotic arm is explored. First, the OCT probe is loaded and moved to multiple local regions for optical scanning. The resulting images are then precisely stitched using a dual-cross-correlation-based translation and rotation registration (DCCTRR) algorithm considering the coordinate information of the robotic arm. This research can serve as a valuable reference for improving the clinical applications of OCT, providing methods to enhance both the user experience and the overall effectiveness of OCT system techniques.
A home-built spectral-domain OCT (SDOCT) system (Fig. 1) and a commercially available 6-joint robotic arm are adopted to test the proposed technique. The transformation matrix from the robot end effector to the OCT coordinate system is calculated using singular value decomposition (SVD). Consecutive local OCT scanning is performed using a home-developed C++ application, and the target pose is converted to a joint pose via an inverse kinematic calculation for robot pose control. To complete a large-scale scan of a chicken breast, 5×5 square grids covering ~8.2 mm×8.2 mm are set, and the overlap ratio can be flexibly adjusted for the registration algorithm mentioned above. Finally, 25 local OCT images are obtained and used as stitches to validate the performance of the proposed technique.
To determine the coordinate transformation from the robotic arm end effector to the OCT coordinate system, the displacement of the steel ball center is measured during the three positional changes of the mechanical arm (Table 1). Regarding OCT image registration, the registration accuracy of 91.07% is achieved using the DCCTRR algorithm, significantly outperforming the kinematic matrix method with the accuracy of 77.20% (Fig. 4). Using the transformed information from the mechanical arm and the DCCTRR method, a large-scale frontal
In this study, the use of a 6-joint robotic arm to load a high-resolution OCT system probe is explored with the aim of achieving large-scale, high-resolution imaging. Because the positioning accuracy of the robotic arm is lower than the OCT imaging resolution, post-image registration (using the DCCTRR algorithm) is required for high-precision image registration. Compared with manual operations, this approach can greatly improve the imaging field without introducing motion artifacts. In summary, robotic arms, image-registration algorithms, and flexible OCT probes are considered in this work to achieve large-scale high-resolution imaging. We believe that this research can serve as a valuable reference for improving the clinical applications of OCT, providing methods to enhance both the user experience and the overall effectiveness of OCT system techniques.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307102 (2025)
High-precision preoperative and intraoperative 3D point cloud registration during pedicle screw placement surgery is crucial for improving surgical safety and success rates. However, preoperative and intraoperative point clouds are obtained using different imaging devices and acquisition techniques, which give rise to challenges concerning noise, variations in densities, and initial poses of the two point clouds. In addition, the independent nature of keypoint features within the point cloud after encoding leads to a lack of global contextual correlation. The absence of feature interaction between keypoints of the preoperative and intraoperative point clouds further reduces the relevance of the features, resulting in suboptimal registration accuracy. To address these issues in preoperative and intraoperative point cloud registration for pedicle screw placement navigation systems and then improve the robustness and accuracy of the registration task, a cross-source point cloud registration network with enhanced attention mechanisms is proposed.
A convolutional neural network is presented for preoperative and intraoperative point cloud registration with enhanced attention mechanisms. First, a voxel-filtering algorithm is applied to adjust the density of the intraoperative point cloud based on the density of the preoperative point cloud. Next, farthest point sampling (FPS) is employed to construct local regions of the preoperative point cloud. For local feature extraction, a multilayer perceptron (MLP) is used to build the encoder. Three feature extraction (FE) and feature propagation (FP) layers are employed to encode the point cloud into keypoints and their corresponding high-dimensional feature representations. The feature aggregation module, consisting of graph self-attention and cross-attention mechanisms, is used to enhance the feature representation of the point clouds. In the graph self-attention mechanism, K-nearest neighbors (KNN) is employed to connect each keypoint in the preoperative point cloud to its neighboring points. By calculating the differences between the keypoint features and neighboring point features, the expression of local geometric features is enhanced. The cross-attention mechanism captures the similarity between preoperative and intraoperative point clouds and identifies deep-level correlations to strengthen the global relevance. Then, the features obtained from cross-attention are enhanced using the graph self-attention mechanism to further improve the local contextual relationships. A similarity function is used to compute point-cloud-matching probabilities to obtain a set of corresponding keypoint pairs. Finally, the random sample consensus (RANSAC) algorithm is applied to eliminate incorrectly matched keypoint pairs. The accuracy of the calculated transformation matrix is improved.
To verify the registration performance of the proposed cross-source point-cloud registration network with enhanced attention mechanisms in surgical navigation of pedicle screw placement, the following actions were conducted: algorithm comparisons, ablation experiments, and registration experiments on noise influenced by intraoperative data. The experiments were conducted on preoperative and intraoperative point cloud datasets, which comprise data from the Capital Medical University Affiliated Hospital and SpineWeb dataset, both of which exhibit substantial initial pose variation and angular changes. (Table 1). The proposed model successfully completes precise preoperative and intraoperative point cloud registration (Fig. 5). To evaluate the performance of the algorithm, the FPS+FPFH and FPS+FastReg methods are compared. The results (Table 2) demonstrate that the proposed method achieves the lowest error in coarse registration, with an average rotational error of 2.87° and a translational error of 3.22 mm, meeting clinical accuracy requirements. Additionally, to further analyze the impact of different attention mechanisms on the overall registration performance, ablation studies were designed to quantitatively assess the contributions of each module to the performance of the network. The results (Table 4) indicate that the combined use of graph self-attention and cross-attention mechanisms significantly improves the expression of point-cloud features and registration accuracy. Noise experiments were conducted to validate the robustness of the proposed model. The results (Table 5) show that although noise degrades performance, the proposed method still achieves good coarse registration accuracy under noisy conditions, demonstrating the robustness of the model to noise interference.
To address the challenges of significant initial poses and density differences during point-cloud registration in a pedicle screw placement navigation system, graph self-attention and cross-attention mechanisms are employed to aggregate and enhance features generated by the encoder. Graph self-attention refines the local feature representation, whereas cross-attention strengthens the global correlations between preoperative and intraoperative point clouds. Consequently, the integration of attention mechanisms allows the model to effectively capture the geometric structure of point clouds, improving both registration accuracy and robustness. The experimental results of the preoperative and intraoperative point cloud registration show that the proposed algorithm improves registration accuracy and efficiency in the navigation system for pedicle screw placement, even in cases with large initial pose differences and cross-source data. In addition, the proposed model demonstrates good coarse registration accuracy under noisy intraoperative point clouds, verifying its robustness against noise interference. Compared to the FPS+FPFH method and FPS+FastReg network model, the proposed model achieves better coarse registration accuracy with shorter executions. This algorithm improves the success rate of point-cloud registration and provides technical support for clinical applications.
.- Publication Date: Jan. 13, 2025
- Vol. 52, Issue 3, 0307103 (2025)
Medical image registration is essential for surgical guidance and lesion monitoring. However, existing deep learning-based registration models typically rely on a single architecture, which limits the ability to leverage the complementary strengths of convolutional neural networks and Transformer models. This often leads to suboptimal registration accuracy and difficulties in preserving the original image topology. To address these challenges, a large kernel multi-scale convolution and Transformer-based parallel registration model (PLKCT-UNet) is proposed.
We develop PLKCT-UNet, a three dimensional (3D) medical image registration model that integrates large kernel convolution and Transformer parallel architecture. In the encoder, the model incorporates three key components. First, a large kernel multi-scale convolution module is designed to enhance the extraction of local detail information and manage large deformations effectively. Second, a 3D Swin Transformer module improves the model's capability to capture long-range dependencies, thereby enhancing generalization performance. Finally, a multi-scale attention aggregation strategy is employed to refine features after dual-encoder channel fusion, further boosting registration accuracy.
To verify the effectiveness of the PLKCT-UNet model, experiments were conducted using the OASIS and LPBA40 datasets. In the comparative experiments, the OASIS dataset was utilized to calculate the degree of overlap between the segmentation masks of the moving and fixed images after registration using seven different methods and the proposed method.Results demonstrate that the proposed algorithm significantly improves registration performance while preserving the integrity of brain structures and maintaining local and spatial information. The algorithm achieves superior registration accuracy and maintains the continuity and consistency of anatomical structures, even under complex deformations. In the ablation experiments, the OASIS dataset was used to assess the contributions of the large kernel convolution (LKC) module, 3D Swin Transformer, and multi-scale attention aggregation (MSAA) module in medical image processing. Results indicate that each module contributes to enhancing the overall network performance. Generalizability experiments were performed using the LPBA40 dataset to validate the robustness of PLKCT-UNet across different datasets. Comparisons with six mainstream algorithms show that PLKCT-UNet achieves higher registration accuracy and generates smoother deformation fields, thereby improving the overall registration quality. These experiments confirm the stability and generalization capability of PLKCT-UNet, highlighting its significant advantages in handling complex deformations.
This study presents PLKCT-UNet, a novel registration model based on LKC and Transformer parallelism. The LKC module addresses sensory field size limitations, balancing detailed and global structures while employing kernel decomposition to reduce computational costs. The Swin Transformer module effectively captures long-range dependencies, enhancing the model's generalization ability. The MSAA module refines spatial and channel features through an attention aggregation strategy, improving dual-encoder feature fusion. On the OASIS dataset, the proposed model demonstrates superior registration performance compared to mainstream methods. Generalization experiments on the LPBA40 dataset further confirm its robustness and versatility. These results establish PLKCT-UNet as a state-of-the-art solution for unimodal medical image registration with broad application potential. Future work will focus on extending the algorithm to multimodal medical image registration and exploring more efficient optimization schemes to further enhance its practicality.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307104 (2025)
Brain tumor is a highly lethal cancer that occurs in human brain tissue, with glioma being one of the most prevalent types originating from glial cells. Malignant brain tumors can damage normal brain tissue and constrict key neural pathways, which may lead to symptoms such as headaches, seizures, vision loss, and limb weakness, significantly affecting the quality of life of patients. Therefore, early detection and treatment are crucial for managing the patient’s condition. Traditional manual segmentation methods are time-consuming, labor-intensive, and require professional knowledge. In recent years, due to the superiority of the convolutional neural network (CNN) in image feature extraction, it has rapidly gained attention in medical imaging. Classic models such as U-Net and V-Net perform well in capturing local and global features and processing three-dimensional (3D) data but exhibit significant computational complexity. Improved models enhance segmentation accuracy through attention mechanisms and hybrid architectures but frequently present challenges such as high memory consumption and slow training speed. Lightweight networks significantly reduce computational costs by optimizing the convolutional structures and reducing the parameter quantity, making them suitable for resource-constrained scenarios. However, there are shortcomings in the segmentation details and contextual modeling. Therefore, research on improving brain tumor segmentation networks is crucial for achieving intelligent healthcare with enormous clinical application potential. Given the above reasons, semiautomatic or fully automatic methods for brain tumor segmentation are being actively developed.
This study proposes a lightweight brain tumor segmentation network that balances global and local information, for high-precision segmentation performance with reduced parameters. This network is based on the U-Net architecture and introduces a semantic flow feature alignment mechanism to replace traditional skip connections. By learning the flow field, the feature maps of the encoder and decoder are spatially aligned to preserve semantic information and spatial details during the fusion process. In the feature extraction stage, the network adopts layered decoupled convolution units as the basic module while introducing shallow-scale perception modules as auxiliary branches to integrate multi-scale contextual information and facilitate adaptive adjustment of features. The scale perception module comprises two parts: multi-head mixed convolution and scale perception aggregation. The multi-head hybrid convolution combines the multi-head attention mechanism with multiscale residual convolution operation, effectively combining the global modeling ability of self-attention with the local feature extraction ability of the convolutional network. Scale-aware aggregation dynamically fuses multiscale features and adaptively modulates attention toward large-scale or intricate information according to regional attributes, thereby producing more discriminative feature representations. In deep feature extraction, the improved hierarchical decoupling convolution unit combined with multiscale convolution operation further enhances the feature capture capability while maintaining low computational complexity.
We performed comparative experiments with other networks on the BraTS2020 dataset and generalization experiments on the BraTS2018 and BraTS2019 datasets. In the BraTS2020 dataset, unlike classical networks (Table 3), our network shows significantly higher Dice index in whole tumor (ET), tunor core (WT), and enhancing tunor (TC) areas than the other two networks. The 95% Hausdorff distance is significantly lower than the other two networks. The comparison of our model with the four popular networks used for brain tumor segmentation show that, the dResUnet model demonstrates the highest accuracy in the Dice index on ET area, the SwinBTS model shows the lowest accuracy, and the proposed method has a moderate effect compared to others. On WT area, the Dice index of SAHNet is 0.36 percentage points higher than the average accuracy, whereas, on TC area, it is about 2.83 percentage points higher than SwinBTS and about 1.08 percentage points lower than ASTNet. The overall effect of our network is at a medium to high level, and regarding the parameter quantity, it is considerably lesser than the other four networks. For lightweight networks, the segmentation performance of our network is superior to the other four segmentation methods. Compared to AD-Net, ET area shows an increase of about 1.12 percentage points in Dice index, while WT area remains the same accuracy. The Dice index in TC area is increased by 2.60 percentage points, and the number of parameters is decreased dramatically. Compared with the DMF network, our model outperforms in three indicators and has a much smaller number of parameters. Compared with HDC network, the number of parameters of our network is greater, whereas the Dice index shows increases of 0.43, 0.36, and 1.92 percentage points in ET, WT, and TC areas, respectively. In ET and WT areas, Dice index of our network is slightly lower than that of HMNet, whereas the accuracy in TC area exceeds that of HMNet by 1.93 percentage points. This indicates that the segmentation performance of the proposed network in TC area is much higher than that of other lightweight networks, while in WT and TC areas are equal. Our network emphasizes on detailed information without sacrificing other accuracies, and the segmentation effect is more accurate than other networks. The average segmentation accuracy of our network achieved on the BraTS2018 and BraTS2019 datasets reached 85.83% and 83.76%, respectively. Our model demonstrates good generalization ability compared with other lightweight segmentation methods (Table 4).
The SAHNet model proposed in this study adopts a layered decoupled convolution module as the basic feature extraction module. Compared with the traditional convolutions, it is more lightweight while maintaining a certain level of accuracy. Simultaneously, the hierarchical decoupling convolution is improved by proposing multi-scale hierarchical decoupling convolution to enhance the expressive power of the model. The feature alignment module is enhanced through the guidance of semantic flow and applied to skip connections, effectively improving the ability of feature alignment by generating flow fields and spatially distorting features. The scale perception module expands the receptive field of the convolution through local residual convolution in MHXC, enabling it to capture richer contextual information at different scales while preserving local features. The SAA module divides feature information into multiple groups and performs cross-group information fusion through lightweight 1×1×1 convolution to achieve global information crossover. The experiments using BraTS2018, BraTS2019, and BraTS2020 show that our method not only outperforms other lightweight networks in segmentation accuracy but also offers better deployment potential on resource-limited devices due to its lightweight design, which is expected to provide more efficient solutions for practical clinical applications.
.- Publication Date: Jan. 17, 2025
- Vol. 52, Issue 3, 0307105 (2025)
In contemporary society, dental diseases affect people of all ages, increasing the workload of dentists. Oral panoramic imaging is a widely used diagnostic tool in dentistry, and doctors must process image data from numerous patients amid their heavy daily clinical workload. However, manually analyzing complex image data is time-consuming, laborious, and susceptible to various human factors, such as fatigue, emotional fluctuations, and differences in professional skills. These factors can adversely affect diagnostic accuracy, delay treatment, and damage patient health. Although artificial intelligence (AI) is initially applied in dental disease detection, most current AI research focuses on single disease or restoration. However, when the number of detection targets increases, the decrease in detection accuracy can hinder practical clinical applications. Therefore, this study applies deep learning to identify key image features for efficient and accurate lesion screening in oral panoramic images using a deep learning network architecture. The purpose is to detect abnormal teeth and restorations including dental cavities, blocked teeth, implants, root canal treated teeth, fillings, crowns, and bridges. Intelligent assistance methods can be used to reduce human errors, accelerate diagnoses, and improve medical quality and efficiency.
This study proposes an intelligent assisted diagnostic network based on the YOLOv8 framework, designing a YOLOv8 model specifically for dental imaging. The purpose is to detect abnormal teeth and restorations including cavities, residual teeth, implants, root canal treated teeth, fillings, crowns, and bridges. Intelligent assistance methods can be used to reduce human error, accelerate diagnosis, and improve medical quality and efficiency. First, to enhance feature extraction capability, we integrated a spatial grouping enhancement (SGE) attention mechanism to enhance the model ability to capture complex oral features. In addition, to address the difficulty of identifying small lesions, a small-object detection layer was added. This layer integrates multiple features and maintains detailed information, thereby enhancing the capability of the model in detecting fine lesions. Subsequently, the model loss function was optimized, adopting the generalized intersection over union (GIoU) loss function to improve the prediction accuracy of bounding box, which further enhanced localization performance. Finally, to reduce the computational burden of improved model, the layer-adaptive magnitude-based pruning
The analysis in Table 2 shows that the SGE attention mechanism performs well in target recognition, outperforming other attention mechanisms in all detection results. Table 4 shows the results of the ablation experiment, indicating that integrating the SGE attention mechanism into the baseline model improves accuracy, recall, and mean average precision (mAP) by 2.4, 2.6, and 1.0 percentage points, respectively. This indicates that the SGE attention mechanism can effectively group features, improve recognition rate, enhance feature extraction, and suppress information interference. After the addition of small-object detection layer, accuracy, recall, and mAP increased by 3.0, 2.4, and 2.1 percentage points, respectively, indicating that the small-object detection layer effectively identifies smaller detection targets and enhances the network ability to recognize small objects. After replacing completing intersection over union (CIoU) with GIoU, the accuracy and mAP increased by 3.6 and 1.2 percentage points, respectively; however, the recall rate decreased by 0.7 percentage points. This indicates that GIoU enhances localization performance and improves recognition accuracy. The final model, YOLOv8-Dental, was developed using the LAMP method, which improved accuracy, recall, and mAP by 5.2, 4.6, and 5.2 percentage points, respectively, while reducing parameters and computational complexity by 2.02×106 and 0.9×109, respectively. Table 5 shows the comparative experiments, indicating that although YOLOv8-Dental performed slightly worse than some models in terms of implants and dental bridges, it still achieved recognition rates of 95.1% and 96.2% for these, respectively. In detecting the remaining five lesions, the proposed model outperformed the other models in average precision (AP) with fewer parameters and a lower computational workload. This ensures high detection accuracy for multiple lesions and maintains the overall detection rate.
This study explored the deep learning-based AI-assisted diagnosis of dental panoramas, aiming to reduce the healthcare burden of dentistry, assist dentists beyond the limitations of subjective judgment, and improve diagnostic accuracy. First, YOLOv8 was used as the base network, which was enhanced by integrating the SGE attention mechanism into its backbone feature extraction network. Second, to detect small target lesions in oral images, a small target detection layer was added to improve recognition accuracy. To further enhance the model bounding box localization accuracy, the GIoU loss function was adopted, which significantly improved the network bounding box regression performance. Finally, the model was pruned using the LAMP method to reduce the number of parameters and computation, thereby improving detection speed. All these optimization strategies were integrated to build the YOLOv8-Dental-assisted diagnosis model. Comparisons and ablation experiments demonstrated the positive impact of each optimization strategy on the diagnosis model. The experimental results showed that the YOLOv8-Dental model achieved a precision rate of 83.9%, recall rate of 87.8%, mAP of 89.8%, and frame rate of 409 frame/s for detecting cavities, blocked teeth, implants, root canal treated teeth, fillings, crowns, and bridges. The validity of the model was verified through physical image detection and heatmap analysis. The results of this study provide theoretical guidance and a methodological reference for deep-learning-based clinical diagnosis, promoting the research on deep-learning-based image-assisted diagnosis of dental diseases.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307106 (2025)
High-power, high-beam-quality lasers have wide applications in industry, medicine, scientific research, and national defense. However, in practical applications, factors such as vibration shocks and environmental temperature changes can cause the cavity mirrors of the laser resonator to deviate, thus resulting in a phenomenon known as detuning. Consequently, the laser resonator no longer functions in the optimal operating state. First, it affects the fundamental mode operation, thereby deteriorating the output-beam quality. In severe cases, this may affect the safe operation of the laser. In recent years, owing to the continuous expansion of laser applications the autonomous monitoring and optimization of lasers have been urgently demanded in scenarios such as unmanned factories, vibration environments, and space environments, where manual maintenance cannot be achieved easily in real time.
In this study, a dual-factor fusion evaluation criterion is proposed that reflects the operating state of a laser by calculating the beam power and morphology in real time, as well as by performing correlation calculations in the theoretical Gaussian optical-field mode, while considering both the mode-field distribution and output power of the laser. Subsequently, a mirror control scheme based on the proximal policy optimization (PPO) algorithm is proposed by combining the mode and intensity of the laser spot with the posture of the cavity mirror using deep reinforcement learning (DRL). This establishes an intelligent agent (resonagent) that can perceive and control the laser cavity. The experimental setup is shown in Fig. 2.
Generally, deviations in the cavity mirror not only decreases the laser power but may also damage certain optical components owing to the deviated optical path. As a side-pumped laser head was used in this experiment, the deviated laser beams may have damaged the end-face seal, thereby affecting the normal output of the measuring pump head. Therefore, we intervened in the active control when the power fluctuates within 3%?5%. For the first 50% power loss, the output power of the laser is more sensitive to the misalignment angle of the cavity mirror (Fig. 3). The health status of the laser is described by a reward function that combines the beam quality and output power. A pretrained deep neural network using the DRL algorithm was employed to control the laser resonant cavity. The results show that the DRL-based laser control agent can intelligently stabilize a misaligned laser resonant cavity within seconds (Fig. 8). This method presents a path advantage over previous algorithms (Fig. 9). Figure 11 shows the stability test results for the resonant cavity agent within 30 min. The average output power is 90.7 W, with a root mean square (RMS) value of 0.95. This indicates that the output power is highly stable over a long period and that the agent's operational decisions regarding the cavity mirror remain stable over time. A spot output with a high beam quality close to the diffraction limit is obtained (Fig. 10).
In this study, an intelligent laser-cavity stabilization technique based on a DRL algorithm is introduced and demonstrated. A deep neural network pretrained using the DRL algorithm was utilized to control the laser cavity. The results show that the DRL-based laser control agent can intelligently stabilize a misaligned laser cavity within seconds. This approach avoids the disadvantages of conventional control methods such as model building, variable decoupling, and parameter tuning. In addition to linear resonant cavities, the agent can be used for various other types of resonant cavities, including folded and ring cavities. Using a simple feedforward neural network architecture requires minimal computational and storage resources, thus rendering it convenient to integrate into embedded or edge-computing devices, which is advantageous for the large-scale deployment of intelligent hardware. Compared with other optimization algorithms, the agent offers more efficient strategies and is thus applicable to higher-dimensional control problems. The perception and operational space of the laser can be extended by integrating artificial intelligence (AI)-based adjustment systems and multiple sensors. Such intelligent lasers can autonomously adjust the optical components based on real-time requirements and environmental changes, thereby achieving highly personalized laser outputs, enhancing the system robustness, and improving the laser performance metrics. In conclusion, the resonant-cavity control agent is crucial for the design, intelligent diagnosis, and state stabilization of future complex laser systems. Furthermore, it is expected to be applicable to the AI diagnosis and maintenance of laser systems in harsh environments such as deep seas or outer space.
.- Publication Date: Jan. 14, 2025
- Vol. 52, Issue 3, 0301001 (2025)
Fluorescent proteins, owing to their excellent optical properties, biocompatibility, high quantum yield, remarkable photostability, and broadband tunability, exhibit significant potential in optical devices. Currently, most fluorescent materials tend to exhibit fluorescence quenching at high concentrations, whereas fluorescent proteins maintain good fluorescence characteristics in solid-state form, thus overcoming the abovementioned limitation. In this study, 2D whispering-gallery-mode (WGM) solid-state fluorescent protein lasers are fabricated via the coffee-ring effect on a silica substrate. Furthermore, to optimize laser performance, we combine solid-state fluorescent proteins with high-quality-factor microbubble cavities, which results in lower lasing thresholds and higher quality factors for microlasers. This study demonstrates the feasibility and practicality of solid-state fluorescent proteins in the fields of photonics and optoelectronics, which allows one to expand their application in solid-state lasers, thereby advancing the research and development of novel lasers.
Solid-state fluorescent proteins are used as gain media to successfully construct biocompatible 2D and 3D WGM lasers. The preparation method is simple and rapid, thus enabling one to effectively control the size and uniformity of geometric shapes. We express and purify mCherry fluorescent protein in Escherichia coli BL21 by transforming the pET30a vector containing the mCherry gene into Escherichia coli. The process involves culturing, inducing expression, cell lysis, and purification using a Ni-NTA gravity column, which results in highly concentrated purified protein. Subsequently, mCherry protein solution is applied to the surface of a 1-mm-diameter silica substrate, which forms an approximately 1-μm-thick 2D solid-state fluorescent protein micro-disk laser via the coffee-ring effect. To further enhance protein-laser performance, we combine solid-state fluorescent proteins with microbubble cavities. We process silica capillaries with a diameter of 140 μm by soaking them in piranha solution, etching them with hydrofluoric acid, and then heating them with hydrogen flame while they are stretched, which results in capillaries with an outer diameter of approximately 35 μm. Subsequently, the treated capillaries are heated with a CO2 laser to form high-quality (Q) factor microbubbles with a diameter of approximately 100 μm and a wall thickness of approximately 1 μm. After injecting the protein solution, the microbubble cavities are rotated and dried to evaporate the water, thus resulting in the uniform attachment of the protein to the inner surface of the microbubble cavities. The optical modes of the 2D and 3D solid-state protein lasers are systematically investigated; the quality factor, threshold, and high-resolution spectra of the lasers are analyzed; and the corresponding simulations are performed, which shows good agreement between the experimental and simulated results.
The fluorescence lifetime, absorption, and photoluminescence spectra of fluorescent protein mCherry are measured
We successfully construct biocompatible 2D and 3D WGM lasers using solid-state fluorescent proteins as gain media. The preparation method is simple and rapid, thus enabling the size and uniformity of geometric shapes to be controlled effectively. The solid-state fluorescent proteins provide sufficient optical gain for the lasers, whereas the formation of 2D micro-disks and 3D microbubbles effectively confines light propagation, thus resulting in low-threshold multimode lasing. The systematic study and simulations show good agreement between the experimental and simulated results. The fabrication process for realizing a transition from 2D to 3D solid-state fluorescent protein lasers is a novel approach for developing biocompatible WGM lasers, thus providing a valuable platform for fundamental research in the field of nanophotonics. This methodology can be extended to other types of fluorescent proteins, which enables the customization of laser devices to satisfy specific requirements across different wavelength ranges. By further reducing the mode volume of the microbubble cavities and increasing the quality factor, one can achieve strong coupling mechanisms between solid-state fluorescent protein excitons and the microcavities. This strong coupling is crucial for investigating polariton lasing under room-temperature conditions with nanosecond pumping.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0301002 (2025)
High-power lasers operating in the 2 μm region have been used extensively in scientific research, national defense, laser medicine, and environmental monitoring. Currently, 2 μm lasers are primarily generated via two technological approaches. One method involves the indirect generation of 2 μm laser through optical parametric oscillation (OPO). However, this method is associated with complex systems and inferior beam quality, thus rendering it difficult to achieve a fundamental-mode output. By contrast, the other approach involves an oscillator emitting a 2 μm region directly based on a gain medium doped with Ho3?. Owing to its simplicity and efficiency, researchers are focusing on its potential application. In thin-disk lasers (TDLs), the thickness of the gain medium is only a few hundred micrometers. Compared with fiber lasers, TDLs allow for a larger radial-longitudinal ratio and have fewer nonlinear effects. Additionally, compared with rod lasers, the large diameter-to-thickness ratio of the Ho∶YAG thin disk ensures an almost one-dimensional heat flow through the disk, thus minimizing thermal effects. In recent years, researchers worldwide have focused on multipass-pumped Ho∶YAG TDLs. In 2021, Tomilov et al. achieved an output power of 112 W with an optical-to-optical efficiency of 54.6% using a 72-pass pump module. Owing to constraints in key technologies such as multipass module design, ultrathin crystal processing, and heat-removal design, studies regarding 2 μm TDLs can not be conducted in China.
We construct a Ho∶YAG TDL using our custom-developed 72-pass module (Fig. 5). First, we analyze the energy levels and fluorescence spectrum of the Ho∶YAG laser. Subsequently, based on the absorption-efficiency curve of the crystal for the pump, we select a Ho∶YAG thin disk, which enables the reflectivity of the crystal to reach 99.98%, with a surface figure of 0.072λ (λ=632.8 nm). Subsequently, a V-shaped cavity is constructed, and the pump spot is rescaled for a high-power continuous wave (CW)output. Finally, the beam quality factor is obtained using the knife-edge method and the laser spectrum is analyzed using an infrared spectrometer.
Based on a pump spot diameter of 3.6 mm, the output power and optical-to-optical efficiency curves as a function of the pump power at different output coupling ratios are shown in Fig. 10. When the pump power is 300 W and the output coupling ratio is 3%, the output power is 129.8 W, the optical-to-optical efficiency is 43.27%, the slope efficiency is 46.98%, and the corresponding pump power density is 2.9 kW/cm2. Figure 11 shows the curves of the output power and optical-to-optical efficiency versus the pump power based on a pump beam diameter of 4.5 mm. The results indicate that a maximum output power of 150.2 W is achieved through beam-spot scaling, which corresponds to a pump power density of 2.0 kW/cm2, and no saturation effects. The optical-to-optical efficiency is 44.18%, which is comparable to that obtained under Dpump=3.6 mm (corresponding to a pump power density of 2.9 kW/cm2), and the slope efficiency is 48.29%. However, because of the limitations of the pump source, the output power cannot be further increased. By fitting the beam-propagation equation to the data shown in Fig. 12, the beam quality factors are measured to be 2.64 and 2.42 in the x- and y-directions, respectively, using the 90/10 knife-edge method. Figure 13 shows that the output spectrum of the Ho∶YAG TDL exhibits two peaks at 2091 nm and 2097 nm. Subsequently, wavelength selection will be performed using a Fabry-Perot (F-P) etalon.
In this study, a custom-developed 72-pass pump module pumped with a Tm-doped fiber laser at 1908 nm is utilized. A 186-μm-thick Ho∶YAG thin disk with a doping mass fraction of 2.5% and a diameter of 10 mm is used. By integrating certain coating techniques, an absorption efficiency of 97.09% is achieved. The surface figure of the Ho∶YAG thin-disk crystal with a diamond heat sink is 0.072λ. In conclusion, a maximum output power of 150.2 W, a slope efficiency of 48.29%, and an optical-to-optical efficiency of 44.18% are achieved. The beam quality factors are 2.64 and 2.42 in the x- and y-directions, respectively. To the best of our knowledge, this is the highest CW power achieved using a Ho∶YAG TDL reported thus far. By increasing the pump power and scaling the pump spot size, a higher output power can be achieved. This study establishes a crucial technological foundation for the development of 2.09 μm pulsed lasers with high average-power levels.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0301003 (2025)
A high-power 7xx-nm semiconductor laser is the core pump source of thulium-doped fiber, alkali metal gas, and metal vapor lasers and has important applications. Compared with 9xx-nm-band near-infrared (NIR) semiconductor lasers, 7xx-nm-band devices usually have waveguide layers and claddings with high aluminum components to maintain good carrier limitation because of their high photon energy; low material mobility leads to increased device resistance and lower carrier injection efficiency. However, high-aluminum component materials easily form oxygen defects during epitaxial growth and cavity surface cleavage, resulting in a low catastrophic light damage threshold power. Therefore, simultaneously achieving high power and high efficiency with 7xx-nm semiconductor lasers is highly challenging.
A laser epitaxial sheet is grown on an N-type highly doped GaAs substrate via metal-organic compound vapor deposition (MOCVD). The fabrication process of the device is similar to that of traditional lasers. First, a 200-μm-wide mesa is formed via photolithography and wet etching. A 200-nm-thick SiO2 electrical insulation layer is grown using plasma-enhanced chemical vapor deposition (PECVD) equipment. A 190-μm-wide current injection window is prepared using the reactive ion beam (RIE) dry method combined with wet etching. A Ti/Pt/Au metal electrode is deposited on the P plane and alloyed. The laser-wafer substrate is thinned and polished, after which the AuGeNi/Au metal electrode is deposited onto the N surface and alloyed via rapid thermal annealing. After the wafer preparation is completed, the wafer is cleaved into a 4-mm cavity length bar by a splitter under the atmospheric environment, and then the cavity surface is passivated and coated. To improve the catastrophic optical mirror damage (COMD) level of the cavity surface, the ZnSe film is deposited after cleaning and passivation, and then the anti-reflection film with a reflectance of 2.8% and the high-reflectance film with a reflectance of 98% are evaporated on the front and back cavity surfaces, respectively. Finally, the bar is cut into a single-tube chip, and the chip is welded onto the AlN heat sink with the P-side down using a chip mounter. The performance of the device is tested. The device is tested at various temperatures using thermoelectric cooler (TEC).
Figure 2 shows the power?current?voltage (L-I-V) characteristics of the laser measured at the 25 ℃ heat sink temperature and continuous operation conditions. The threshold current of the laser is 1.24 A, and the corresponding threshold current density is 155 A/cm2. The slope efficiency of the laser is 1.33 W/A, the series resistance is 15.5 mΩ, and the continuous power is 13 W at a current of 11 A; the corresponding power conversion efficiency is 66%, and the maximum photoelectric conversion efficiency is 66.6%. Figure 3(a) shows the far-field distribution measured by the laser under a continuous current at room temperature and 10 A. The vertical divergence angle is 32.2°, and the vertical far-field divergence angle of the beam with 95% power ratio is 49.8°. The full width at half-maximum of lateral far-field divergence angle and lateral far-field divergence angle (B) of the beam with 95% power ratio are 6.3° and 7.4°, respectively. Figure 3(b) shows the laser lasing spectrum measured at room temperature and a current of 10 A, with a visible peak wavelength of 780.83 nm and a full width at half-maximum of spectrum of 1.77 nm. The L-I-V characteristics of the device under quasi-continuous operation conditions (pulse width of 100 μs) are also tested, as shown in Fig. 4. The peak power of the device at a current of 12.7 A is 16.3 W, the corresponding conversion efficiency is 69%, and the maximum power conversion efficiency is 70% (when the output power is 14.3 W). Figure 5 shows the lateral far-field distribution and lateral divergence angle with respect to temperature. When the heat sink temperature increases from 15 ℃ to 60 ℃, the change in B is almost 0. At 30 ℃, the lateral far-field development exhibits large broadening. The lateral far-field distribution of the laser at 25 ℃ and under different currents is shown in Fig. 6. As the current increases, the lateral far field of the laser gradually widens. At a current of 2.0 A, B is 5.2°, and when the current is increased by 9.0 A, B increases to 7.2°. The output characteristics of the laser are measured in the temperature range of 5?60 ℃, and the operation current is continuous at 5 A. The changes in the threshold current and slope efficiency of the laser with respect to temperature are shown in Fig. 7. The two intervals of 15?30 ℃ and 35?60 ℃ are selected to calculate the characteristic temperature, and
In this study, a high-power semiconductor laser with an operation wavelength of 780 nm is developed. Using a GaAsP quantum well to increase the barrier height and suppress carrier leakage, a high-efficiency epitaxial structure with low internal loss is obtained in combination with the design of an asymmetric large optical cavity. The prepared 200-μm stripe laser achieves a quasi-continuous output power of 16.3 W and a continuous output power of 13 W, and the corresponding photoelectric conversion efficiency reaches 69% and 66%, respectively. The lateral far field of the laser does not change significantly with temperature but widens significantly with an increase in the working current. By testing the threshold current and slope efficiency of the device at different temperatures, the characteristic temperatures
- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0301004 (2025)
Accurate power measurement is the basis of high-power laser applications, and ensuring the quality of laser-processed products is crucial. Owing to the progress in fiber-laser technology, the maximum output power afforded by industrial-grade fiber lasers has increased continually. A set of ultrahigh-power laser-measurement devices based on the principle of light pressure was established to measure the output power of a 200 kW industrial-grade fiber laser.
In this study, a focused laser beam was incident at a small angle to a light-pressure power meter (LPPM) after being output from the lens set; furthermore, it was absorbed by the laser dump after being output from the LPPM, as shown in Fig. 1. The LPPM was equipped with three ultrahigh-reflectance, high-damage-threshold mirrors, whose reflectance exceeds 99.995% in the 950?1100 nm waveband. Two rectangular mirrors were mounted on the top of the LPPM at an angle of 110°, and another 90-mm-diameter mirror was connected to the weighing module.
We performed power measurements at different levels, as shown in Fig. 2(a). The measurement repeatability is better than 0.1% (calculated using the polar deviation method), and the response time of 0%?100% power is less than 3 s. The full-power output is 200.50 kW, with a response time of 2.6 s, as shown in Fig. 2(b). The measurement uncertainty of the laser power was evaluated and calculated based on the guide to the uncertainty in measurement (GUM) and the Monte Carlo method (MCM), as shown in Fig. 3. The rapid decrease in the measurement uncertainty in the power range of 3?10 kW is primarily caused by the gradual decrease in the contributions of the mass-measurement uncertainty component and resolving power to the measurement uncertainty as the measured power increases. When the laser power exceeds 10 kW, the variation in the measurement uncertainty stabilizes and is better than 0.76% (confidence factor k = 2).
We report the power for industrial-grade fiber lasers measured by an LPPM. This LPPM realizes highly accurate laser power measurements traceable to the Système International (SI) basic unit (kg).
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0315001 (2025)
The nervous system serves as the primary communication system in animals. Neurons, the fundamental structural and functional units of this system, communicate through a combination of electrical and chemical signals. Deciphering and comprehending diverse neural activities and circuit functions are of paramount importance in the realms of fundamental brain science, the diagnosis and treatment of neurological disorders, and brain-computer interface applications. Integrating optogenetics and electrophysiology into an optoelectric neural interface offers a synergistic approach to studying complex brain circuits and unraveling their intricate dynamics, enabling researchers to observe and modulate neuronal activity with precision. This capability opens new avenues for investigating fundamental questions about how different brain regions communicate and contribute to behavior. By combining optogenetics and electrophysiology to create advanced optoelectric neural interfaces, researchers can gain unprecedented insights into brain functions.
An optogenetic stimulation system was integrated with an electrophysiological recording system to measure photoelectric artifacts. A 473 nm fiber-coupled laser served as the light source for optogenetic stimulation, with a pulse generator employed to control the laser pulses. Electrophysiological signals were recorded using an Intan 1024-channel electrophysiological recording system. The optoelectrodes were fabricated using tapered optical fibers and ultra-flexible electrodes, which were then implanted into either the mouse brain or an agarose gel phantom to capture photoelectric artifacts in vivo or in vitro. The ultra-flexible neural electrode was fabricated using planar semiconductor technology, incorporating a polyimide insulation layer and a gold wire layer, as described in our previous publications. In addition, the electrode surface was modified with PEDOT∶PSS to enhance electrophysiological recording performance. The tapered optical fiber, supplied by Optogenix, featured a numerical aperture (NA) of 0.39, core size of 200 μm, and an active length of 2.5 mm. The optoelectrode probe was assembled by temporarily bonding the optical fiber to the ultra-flexible electrode using polyethylene glycol (PEG, mPEG=400000 u). The optical performance of the fabricated optoelectrode was characterized through theoretical calculations using LightSpread software, as well as experimental verification in vitro and in vivo. In the in vitro measurements, powdered milk, agarose, and sodium fluorescein were used to simulate tissue scattering and assess the light-field distribution of both tapered and flat port fibers in a scattering medium. For the in vivo demonstrations, optoelectrodes were implanted into the mouse CA1 brain region to perform concurrent optogenetic stimulation and electrical recording. Electrophysiological signals were filtered and analyzed using MATLAB software. The peak value of the photoelectric artifact was defined as the maximum absolute voltage observed during the optical pulse. The power spectral density (PSD) of the local field potentials during optical stimulation was obtained using a short-time Fourier transform, and the Mountainsort4 algorithm was employed for peak potential cluster analysis to isolate the waveform and timestamp of the action potentials.
We designed and fabricated a novel optoelectrode that combines a tapered fiber with an ultra-flexible electrode (Fig. 1). The tapered fibers exhibit an extended illumination range and a more uniform intensity distribution compared to flat-port fibers in a scattering medium (Fig. 2). In vitro experiments reveal variations in photoelectric artifacts across different channels, optical powers, and media types, with the peak values of photoelectric artifacts increasing alongside higher concentrations of milk powder and laser power. Power spectral density analysis indicates that photoelectric artifacts predominantly occur within the frequency range below 10 Hz (Fig. 3). During in vivo experiments, we analyzed the impact of light stimulation on the frequency bands of local field potentials (LFP), ranging from 0 to 300 Hz, and action potentials (AP), ranging from 300 to 7500 Hz. Our findings indicate that photoelectric artifacts primarily affect the LFP signals. Additionally, we longitudinally assessed the impedance evolution of the optoelectrode post-implantation and observed a gradual increase in average impedance during the first week, followed by stabilization over the subsequent three weeks. The peak value of photoelectric artifacts initially increases during the first two weeks, followed by a gradual decline over the next two weeks. Power spectral density analysis reveals that light stimulation predominantly influenced electrophysiological signals below 10 Hz, consistent with the in vitro testing results (Fig. 4). Finally, we validated the capabilities of optogenetic stimulation and synchronous electrophysiological recordings using the optoelectrode.
In this study, we present the design and fabrication of a novel optoelectrode that combines a tapered fiber with an ultra-flexible neural electrode. A comparative analysis of the optical power density and optical field distributions in a scattering medium was conducted between the tapered flat-port fibers, revealing the superior optogenetic stimulation performance of the tapered fiber. Moreover, we investigated the impact of photoelectric artifacts from the optoelectrode on electrophysiological recordings. The in vitro test results reveal variations in photoelectric artifacts across different electrode channels, environmental conditions, and laser powers. In vivo experiments demonstrate that optical stimulation primarily influences the LFP band, whereas the electrochemical impedance of the optoelectrode gradually increases and eventually stabilizes over time. The peak value of photoelectric artifacts varies depending on the duration of implantation. Photoelectric artifacts primarily induce interference within the frequency range below 10 Hz. To mitigate these artifacts, future studies could explore the utilization of coating materials such as PBK, PGO, and Pt-Black/PEDOT-GO. In addition, incorporating principal component analysis or machine learning techniques during data processing, employing a longer-wavelength excitation light source, or adjusting the electrode distance from the light source are all avenues worth investigating.
.- Publication Date: Jan. 14, 2025
- Vol. 52, Issue 3, 0307301 (2025)
With the increasing number of diabetic patients, diabetic retinopathy has become a leading cause of vision loss worldwide. Currently, 532 nm panretinal laser photocoagulation is a primary treatment method for diabetic retinopathy. Because of the difficulties with existing technology in directly measuring the temperature distribution of the fundus during treatment, improper selection of laser parameters may damage normal fundus tissue and affect vision. Accordingly, a real three-dimensional (3D) entire-eye model is constructed using fundus optical coherence tomography (OCT) images, and the effects of the structural differences in fundus tissue on the fundus temperature under different laser incidence angles are studied via numerical simulation to provide a reference for the selection of laser parameters in actual treatment.
OCT images of the retina in the OCTA-500 dataset are segmented to obtain the key tissue layers for photocoagulation therapy, and a 3D voxel model of a real fundus is constructed. Anterior tissue is then added to establish a complete 3D voxel model of the eyeball. A 3D voxelized Monte Carlo simulation (MCVM) is next performed to obtain the propagation path and absorption distribution of the 532 nm laser in the eye. Based on the simulated absorption distribution results, the Pennes biological heat transfer equation is used to calculate the fundus temperature under a 532 nm laser. We are able to study the effects of the incidence angle and fundus structural differences on the fundus temperature distribution by changing both the photon incidence angle in the MCVM and the OCT image data of the fundus.
This study conducts a 3D MCVM to analyze the photon propagation characteristics derived from an eye model. The results indicate that the photon escape and absorption rates within the ocular tissues are 8.9%±0.06% and 91%± 0.05%, respectively. Notably, the energy absorbed by the retinal tissues accounts for approximately 94% of the total absorption, with the anterior segment of the eye contributing only 6%
We construct a realistic 3D eyeball model utilizing OCT images and employ a 3D MCVM to simulate the distribution of laser energy within fundus tissue. The simulation results enable us to calculate the temperature variations under different laser incidence angles and fundus structures. Our findings show that the laser propagation trajectory in the anterior segment of the eye remains largely unchanged, with only 6% of the total light being absorbed by this region. By contrast, 94% of light absorption occurs in the fundus tissue, predominantly within the retinal pigment epithelial layer. This aligns with the mechanisms observed in actual photocoagulation treatments. In addition, we find that the refractive and scattering effects of ocular tissues significantly influence laser behavior. Specifically, a mere 1° deviation in the laser incidence angle can result in an error of approximately 11% in the peak temperature rise in the fundus. This underscores the importance of considering the incidence angle to ensure that simulation results accurately reflect the dynamics of actual photocoagulation procedures. Finally, variations in fundus structures are found to substantially affect the temperature simulation outcomes, with potential errors in temperature rise of up to 13%. Thus, the development of 3D fundus modeling based on OCT images is critical for enhancing the adaptability of numerical simulations to diverse patient anatomies. The methodologies and findings of this study can serve as valuable references for optimizing laser parameter selection in panretinal photocoagulation therapy.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307201 (2025)
Clustered regularly interspaced short palindromic repeats (CRISPR) technology offers unprecedented precision in gene editing and nucleic acid detection. CRISPR/Cas systems are derived from bacterial adaptive immune responses and have been ingeniously adapted for the programmable recognition and cleavage of specific nucleic acid sequences. Their integration with either traditional nucleic acid amplification methods [e.g., polymerase chain reaction (PCR) and recombinase polymerase amplification (RPA)] or advanced nanotechnologies [e.g., surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), and electrochemistry] enhances detection sensitivity and expands the applicability of these platforms, particularly in point-of-care testing and resource-limited environments. This review examines the convergence of CRISPR with traditional nucleic acid amplification techniques and its innovative integration with nanotechnology to showcase a significant leap in nucleic acid detection for disease diagnosis, pathogen examination, and food safety inspection.
This review investigates the mechanistic details of CRISPR/Cas9, CRISPR/Cas12, and CRISPR/Cas13 systems by illustrating the roles of these technologies in recognizing and cleaving specific nucleic acid sequences. Furthermore, the integration of CRISPR/Cas systems with traditional isothermal amplification techniques, such as PCR and RPA, has led to the development of rapid and portable detection platforms, such as SHERLOCK, thus demonstrating high sensitivity and specificity at reduced costs. In parallel, the convergence of CRISPR with nanotechnologies has opened new avenues for detection. For instance, the fusion of CRISPR with nanotechnologies, including SPR, SERS, and electrochemistry, has introduced novel detection modalities with improved sensitivity and speed. The combination of the specificity of CRISPR with the signal amplification properties of nanoparticles has resulted in the creation of biosensors with single-molecule detection capabilities and rapid, visual readouts.
The integration of CRISPR with both traditional and nanotechnology-based nucleic acid detection methods heralds a new era in diagnostics. The future of CRISPR-based detection technologies is likely to focus on enhancing specificity, reproducibility, and clinical adaptability while exploring new avenues in biomedical applications. The synergy between CRISPR and nanotechnology is anticipated to yield portable, highly sensitive diagnostic devices and integrate with smartphone technologies and artificial intelligence for real-time, on-site disease diagnosis. As research continues, the prospects for CRISPR-based nucleic acid detection are promising and could revolutionize clinical diagnostics, disease monitoring, and personalized medicine.
.- Publication Date: Jan. 10, 2025
- Vol. 52, Issue 3, 0307202 (2025)
As society evolves, individuals increasingly prioritize their health, leading to heightened demands for disease diagnosis and treatment. The pursuit of high-quality and efficient treatment is essential for achieving this goal. As an emerging treatment strategy, photodynamic therapy (PDT) has been proven to be a minimally invasive therapy with strong controllability and spatiotemporal resolution, demonstrating notable clinical potential in anti-cancer and anti-infection treatment.
The therapeutic agent in PDT, known as a photosensitizer (PS), operates through a mechanism illustrated through the Jablonski energy level diagram (Fig. 1). Under appropriate wavelength light irradiation, PSs become excited from the ground state (S0) to the singlet excited state. Among these excited states, the lowest singlet state (S1) plays a crucial role in subsequent photophysical processes, following Kasha’s rule. When excitons return to their ground state through radiative transitions, they release fluorescence, which enables PS localization and provides guidance for subsequent PDT. Excitons can also transition from S1 to the lowest triplet state (T1) through an intersystem crossing (ISC) process, subsequently generating reactive oxygen species (ROS). These reactive oxygen species oxidize surrounding biomolecules and produce cytotoxicity in target cells or bacteria. In addition, PSs in the excited state can return to S0 through non-radiative decay, generating heat and achieving a combination of photothermal therapy (PTT) and PDT in some special cases.
Despite significant advancements in PDT during recent years, PSs still commonly feature planar conjugated structures, resulting in high hydrophobicity. This characteristic means that PS degradation or elimination often requires extended periods after PDT. During this period, residual PSs may continue generating reactive oxygen species upon natural light exposure, potentially damaging normal cells and tissues, and eliciting acute inflammatory responses and side effects, thereby limiting their clinical utilization. This review focuses on the safety aspects of PSs in phototherapy, using representative cases to analyze general strategies for enhancing their metabolism and degradability via rational molecular design.
Enhancing the metabolic potential of PSs can effectively mitigate postoperative adverse effects. The kidney, a crucial organ in human physiology, serves as a primary filter for metabolic waste and reabsorption of essential substances, thereby preserving internal homeostasis. PSs designed for renal clearance must address postoperative excretion requirements, with their size remaining below the renal filtration threshold of approximately 6 nm for effective renal metabolism. A prevalent approach to enhancing renal clearance (RCE) of PSs involves incorporating one or more hydrophilic moieties, including polyethylene glycol (PEG) chains (Fig. 2), charges (Fig. 3), and morpholine group (Fig. 4), to control the morphologies and sizes in physiological environments to satisfy the requirements of renal metabolism. A recent alternative approach involves constructing PSs using readily oxidizable groups, which upon oxidation form polar bonds, thereby enhancing the hydrophilicity of the product and subsequently accelerating the metabolic rate of the PSs (Fig. 5).
In recent years, degradable PSs have been proposed that can undergo degradation via ROS oxidation following diagnosis or treatment, thereby mitigating potential side effects. Furthermore, the degradation products exhibit smaller sizes than their precursors, facilitating expedited elimination from the body. A common strategy for designing such degradable PSs, apart from employing supramolecular approaches (Fig. 6), involves introducing π-conjugated bridges susceptible to oxidation and rupture into PSs, exemplified by methyl imidazole (Fig. 7), anthracene bridges (Fig. 8), conjugated double bonds (Fig. 9), and diketopyrrole (Figs. 10 and 11). Generally, the degradation process encompasses self-degradation and biodegradation. In the self-degradation process, PSs degrade through self-generated ROS upon excitation, while biodegradable PSs undergo degradation by endogenous ROS, leading to different application scopes: self-degradable PSs are suitable for intratumoral administration, while biodegradable PSs are suitable for systemic administration. Recent development of PSs with both degradation modes (Fig. 12) ensures complete degradation, further enhancing postoperative safety. Besides above examples, researchers report the use of unstable non-conjugated linkers to construct degradable pseudo-conjugated polymers (Fig. 13). For this type of PSs, degradation is unlikely to destroy the conjugated structure, thereby accelerating metabolism without function loss, which is an effective strategy to improve PDT safety.
In this study, the latest advances in improving the metabolism or degradability of PSs to enhance PDT safety are reviewed. Generally, introducing highly hydrophilic groups onto PSs to control their morphologies and sizes in physiological environments is the most commonly used method to improve their renal clearance rate, while using easily oxidizable conjugated units (such as methyl imidazole and anthracene ring) as conjugated bridges to construct PSs is key to endowing them with degradability. In theory, the approach of “degradation first, followed by metabolism” appears advantageous over metabolism alone, because PSs quickly lose their photosensitization during degradation, resulting in reduced impact on the human body post-PDT. In addition, organisms eliminate the degradation products more easily. However, it is important to note that the metabolizable or biodegradable PSs remain in the laboratory study phase. Before clinical promotion, their detailed biocompatibility, pharmacokinetics, detailed metabolic pathways, long-term side effects, etc. require strict evaluation, which is a time-consuming and expensive task. As concluding remarks, we expect that this review will inspire the development of PSs with heightened biosafety profiles.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307203 (2025)
In the biomedical field, traditional caries treatment often relies on tooth-grinding machines. However, the significant thermal effects produced by the high-speed friction of drill irreversibly damage the tooth surface. Therefore, in this study, femtosecond laser direct-writing processing technology is used to replace traditional grinding machines for caries treatment. The influence of laser scanning power, speed, and frequency on tooth surface cavity characteristics is studied using a femtosecond laser with high controllability and flexible programmability. The results demonstrate that the scanning power and frequency of the femtosecond laser are positively correlated with the hole depth and bottom roughness, whereas the scanning speed is negatively correlated. The experimental results confirm the feasibility of using a femtosecond laser to remove necrotic dental tissues. The present study facilitates the use of lasers in dental analysis and treatment and contributes to the understanding of the mechanism of laser-tooth interaction.
Carious teeth are first immersed in an acetone solution for 6 h to remove grease and dirt from the carious surface. The caries are then rinsed with anhydrous ethanol to wash away residual tissue and acetone solution. After pretreatment, a circular pattern with a diameter of 1 mm is drawn, and the laser scanning mode is set to “horizontal scanning + vertical scanning”. The 3D moving table is adjusted so that the laser focus is located on the tooth surface. The laser scanning distance, laser scanning speed, laser scanning power, pulse repetition frequency, energy of a single pulse, and laser scanning number are set to 0.01 mm, 5 mm/s, 500 mW, 1 kHz, 500 J, and five, respectively. In this experiment, only the scanning speed, laser power, and number of iterations are varied, and eight control groups are set for each variable. The teeth are processed after setting the parameter settings, and subsequently, the morphology of the processed holes is observed and characterized using a laser confocal microscope.
The morphology of the femtosecond laser-processed holes is observed using a laser confocal microscope, and the holes are constructed and characterized by a three-dimensional model using a analysis software. The relationship between the different processing parameters and hole depth is analyzed and plotted (
In summary, we use human teeth as the target to investigate the effect of a femtosecond laser on tooth structure under different processing parameters. By adjusting the laser scanning speed, laser scanning number, and power of the femtosecond laser, we process holes with different depths and roughnesses on the tooth surface. Subsequently, we characterize these holes to determine the relationship between the femtosecond laser processing parameters and changes in the tooth structure. The experimental results indicate that femtosecond lasers have broad application prospects in dentistry, and the optimization of their processing parameters can significantly improve the safety and efficacy of dental treatment, thereby providing new ideas and methods for developing future dental treatment technology.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307204 (2025)
China has a high prevalence of eye diseases, with retinal conditions, such as diabetic retinopathy and macular degeneration, posing significant threats to vision. In current clinical practice, laser therapy is commonly used to treat these retinal diseases. However, improper selection of laser parameters during treatment can lead to adverse effects, such as vision damage, in over half of the cases. Therefore, it is crucial to develop a heat transfer model for laser therapy of retinal diseases to assist physicians in adjusting laser parameters and formulating appropriate treatment plans for different patients. Previous models of eye have led to various simplifications and cannot accurately simulate the multiscale intraocular heat transfer processes from the macroscopic whole eye to the microscopic retina during laser treatment. To address this issue, in this study, a coupled bioheat transfer model of the human eye is developed, providing a basis for selecting laser parameters in retinal surgeries.
In this study, a coupled bioheat transfer model of human eye is developed. For the heat transfer process at the whole eye scale, Penne bio-heat transfer equation is employed. For the microscopic retinal scale, different parts of the fundus are modeled as porous media comprising biological tissues mixed with chromophores, and a two-temperature equation is established to represent the non-equilibrium heat transfer between the chromophore tissue and surrounding tissue matrix. By combining Penne bio-heat transfer equation with a two-temperature model, this model enables the simulation of laser retinal surgery across different time scales. In this model, calculations are performed using ANSYS software. First, a 3D geometric model of the entire eye is created using SolidWorks, followed by the division of the fully coupled eye model into polyhedral meshes using Fluent Meshing. Fine meshes are applied to narrow tissue structures, such as cornea, retina, choroid, and sclera, while coarser meshes are used for thicker tissue structures such as vitreous body and lens. The finite volume method in the ANSYS Fluent 2022 solver is used to solve the discretized equations. A double-precision coupled solution approach with a second-order implicit scheme is adopted, and the energy equation is solved using a second-order upwind scheme. After grid independence verification, the final model employs 7.02 million polyhedral cells.
The results show that thermotherapy via transpupillary thermotherapy can easily lead to retinal damage due to its longer treatment time. This in turn increases the risk of local recurrence and scleral extension, often resulting in suboptimal surgical outcomes. Panretinal photocoagulation can effectively heat the three light-absorbing layers of the fundus under quasi-thermal equilibrium conditions, causing thermal coagulation of damaged retinal tissue. However, this approach can damage retinal photoreceptors, potentially leading to scarring and anatomical disruption of the retina. Subthreshold diode micropulse, which uses lower laser energy, only thermally stimulates the release of cytokines from the retinal pigment epithelium (RPE) layer without causing significant damage to the retinal photoreceptors. Therefore, it is an effective treatment for retinal diseases such as macular degeneration.
This study addresses the issue that existing models are still unable to accurately simulate the thermal process of multi-scale lesion targets in retinal laser surgery. A fully coupled model of the entire eye has been developed, which can simulate the thermal processes of retinal laser surgery across the full time scale, from microseconds to seconds. The model couples Pennes bioheat transfer equation with a two-temperature non-equilibrium heat transfer model in porous media to calculate the thermal effects of typical retinal laser surgeries, including transpupillary thermotherapy (TTT), panretinal photocoagulation (PRP), and subthreshold micropulse diode laser (SDM) therapy. This model aids in optimizing laser surgery parameters for retina. The simulation results indicate that TTT, due to its longer treatment time, sometimes leads to retinal damage, increasing the risk of local recurrence and scleral extension, often resulting in poor surgical outcomes. Furthermore, PRP effectively heats the three light-absorbing layers of the fundus under quasi-thermal equilibrium conditions, but it may cause damage to adjacent retinal matrix tissues (photoreceptors), leading to night vision loss, scarring, and anatomical disruption of the retina. In SDM therapy, the use of lower energy only stimulates the release of cytokines from the RPE cells during recovery, without causing significant damage to the retinal nerves, making it an effective treatment for retinal diseases such as macular degeneration.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307205 (2025)
Port-wine stain (PWS), a prevalent skin disease affecting the appearance of patients, arises from vascular malformations within the dermis of skin tissue. Laser surgery is a frequently used method for treating PWS. Based on the principle of selective photothermolysis, lasers with a specific wavelength can cause permanent thermal injury to vascular lesions without causing damage to the overlying normal epidermis. However, melanin in the epidermis absorbs laser energy, potentially leading to unnecessary epidermal heating and resulting in complications such as necrosis or undesired pigmentation. Pre-cooling the epidermis with cryogen spray can effectively mitigate or even eliminate thermal injury. Although fluoride-based refrigerants are commonly used, they have limitations in terms of their cooling efficacy and environmental compatibility. Carbon dioxide (CO2), a nontoxic, environmentally friendly, nonflammable, and readily available natural cryogen, is a promising alternative. Existing research on CO2 spraying has primarily focused on its cleaning and steady-state heat dissipation capacities, diverging from the context of cutaneous laser surgery. Thus, this study aims to investigate transient CO2 spray cooling by analyzing the effects of spurt duration (40?100 ms) and spray height (20?40 mm) on the cooling efficacy and radial variations in cooling. Furthermore, a modified Nusselt number is employed to extrapolate the acquired cooling capacity to the surfaces of the other materials. Subsequently, the study integrates spray cooling with laser thermal effects to calculate the temperature distribution within the skin tissue, thereby evaluating potential thermal injury. The findings of the CO2 spray cooling and thermal injury estimation are expected to provide valuable insights for clinical applications.
In this study, an experimental system for open-loop transient spray cooling is developed. Liquid CO2 is supplied from a CO2 cylinder, and nitrogen gas is used to regulate the pressure of liquid CO2, which compensates for the flow pressure losses along the pipe to avoid cavitation within the pipe. The customized solenoid valve, data acquisition (DAQ) board, and corresponding LabVIEW program work together to control the spray duration. The spray height is adjusted by using a three-dimensional positioner. An epoxy resin board is employed as the skin phantom because its thermal and physical properties are similar to those of human skin. A high-speed camera is used to record the complete spray process, and four thermocouples are used to measure the surface temperatures of the epoxy resin board. Surface temperature data are used to calculate heat fluxes, heat transfer coefficients, and modified Nusselt number correlations. Based on the simplified Pennes equation describing bioheat transfer, a numerical simulation is conducted to model skin tissue undergoing sequential spray cooling and laser irradiation. The temperature distribution within the skin tissue is calculated, and thermal injury is estimated using Arrhenius integral analysis.
As illustrated in Fig. 5, the transient CO2 spray process can be categorized into three stages: developing, stable, and decay regimes. Extending the spurt duration of CO2 spray cooling leads to a lower surface temperature. However, the maximum heat flux is constrained by the mass of dry ice particles participating in the surface heat exchange per unit time. Continuously increasing the spurt duration after exceeding the point at which the spray reaches a stable regime does not further enhance the maximum heat flux (Fig. 6). Spray height primarily influences the mass loss of dry ice particles owing to evaporation and sublimation during flight. Reducing the spray height results in a larger mass of dry ice particles participating in the surface heat transfer, which usually means a lower surface temperature and higher maximum heat flux (Fig. 7). Below a certain spray height, further reductions do not increase the maximum heat flux. The limiting factor shifts from the mass of dry ice particles participating in the heat exchange per unit time to the low thermal conductivity of the epoxy resin. Furthermore, CO2 spray cooling exhibits significant radial decay owing to the lower concentration of dry ice particles away from the spray center (Fig. 8). Thermal injury estimation (Figs. 9?11) reveals that CO2 spray cooling effectively protects the epidermis. With a spray height below 40 mm and duration of 100 ms, epidermal thermal injury is avoided. However, shorter durations and higher spray heights may lead to thermal injuries at the periphery of the cooled area. This outcome can be further optimized through additional measures, such as employing a multiorifice nozzle and decreasing the radius of the laser spot.
This study experimentally determines the cooling capacity of transient CO2 spray and uses simulations to estimate its protective effect on the epidermis during laser therapy. A lower surface temperature is realized by extending the spray duration and decreasing spray height. The maximum heat flux is primarily influenced by the mass of dry ice particles participating in the surface heat exchange per unit time, although this influence diminishes with decreasing spray height. A radial decline in the dry ice particle concentration from the spray center results in a significant radial attenuation of CO2 spray cooling capacity. Additionally, with appropriate spray and laser parameters, CO2 spray cooling can protect the epidermis from thermal injury, and there is room for further optimization.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307206 (2025)
Small incision lenticule extraction (SMILE) has garnered significant attention due to its advantages of small incisions, absence of corneal flaps, and preservation of cornea integrity. During SMILE, a laser is used to cut the corneal stromal layer, and the refractive lenticule is obtained and removed to correct myopia. The corneal incision alters the corneal structure, reducing its biomechanical strength and resistance to deformation. Latrogenic keratectasia occurs when the biomechanical strength is below the threshold required to maintain corneal shape. Thus, investigating the biomechanical changes in the cornea after SMILE surgery has become a key research area in the field of refractive surgery. Elastic modulus is a primary factor affecting the biomechanical changes of the cornea. Some studies have indicated changes in corneal elastic modulus after SMILE. However, there are notable variations among patients. The refractive lenticule and corneal cap thickness differ considerably in clinical practice. Consequently, the quantitative analysis of the corneal elastic modulus after SMILE remains controversial. This study aimed to quantitatively examine the influence of corrected refraction and corneal cap thickness on the corneal elastic modulus using the finite element method (FEM) after SMILE.
This study used Corvis ST technology and corneal topographic maps. A parametric modeling approach was applied to reconstruct a preoperative three-dimensional geometric model of rabbit eyes, including the lens, ciliary body, and aqueous humor. Additionally, the cutting surface and incision were fitted using point cloud data. Seven postoperative SMILE models with different corrected refractions were created while maintaining the same corneal cap thickness. Furthermore, four models with different corneal cap thicknesses were reconstructed with corrected refraction being maintained in the range of the -3 D and -6 D. The finite element software COMSOL Multiphysics 5.6 was used to simulate the corneal shear-wave optical coherence elastography (OCE) experiment. The intraocular pressure was set to 10 mmHg, which is consistent with the experimental intraocular pressure. A transverse propagating shear wave was generated in the cornea after transient excitation at the excitation source. The central point of the shear-wave vibration source was designated as the origin, and multiple detection points were set on its right side. The temporal displacement data were extracted at the detection points. The phase velocity algorithm was applied to obtain the dispersion curve of the phase velocity for the shear wave. The corneal elasticity was then quantified. Finally, the effects of corrected refraction and corneal cap thickness on the simulated corneal elastic modulus after SMILE were examined. The corneal elasticity in rabbit eyes after SMILE was measured non-invasively using ARF-OCE experiments. The obtained value of the corneal elastic modulus was used to validate the simulation results.
The results indicated that the simulated corneal Young’s modulus increased significantly by 192.26% when the corrected refraction changed from 0 D to -6 D. Furthermore, the result of the curve-fitting of shear-wave velocity at various corrected refractions was good (
A personalized three-dimensional FEM of rabbit eyes was reconstructed. The corneal OCE experiments in rabbit eyes after SMILE were simulated using the FEM and validated using ARF-OCE experiments. The findings indicate that increased corrected refraction and corneal cap thickness lead to increased simulated corneal elastic modulus. The former has a more significant influence, demonstrating a nonlinear increase. The latter has less significant effects than the former. This conclusion was also confirmed by the ARF-OCE experiments. This study theoretically examined the influence of single factors such as correction refraction on corneal elastic modulus and achieved an accurate quantification of corneal elasticity using FEM. This study provides theoretical insights into accurate experimental measurement of corneal elasticity and serves as a reference for the clinical characterization of elastic modulus.
.- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0307207 (2025)
Focused pulsed laser has been widely used in a wide range of applications such as element composition analysis, microsurgeries, microfluidic operations, and in clinical laser surgery for the disintegration of kidney stones and intravascular plaque treatment, among other procedures. In many of these scenarios, cavitation bubbles are generated in semi- or fully confined liquids and play a dominant role. The strong interactions of bubbles with the surrounding confined environment lead to complex dynamics of both the bubbles and elastic boundaries, which can contribute to the desired effect but can also generate undesired side effects. Therefore, it is of practical importance to explore the influence of the confinement effect on bubble dynamics. In recent years, intensive research has been conducted on the laser-induced bubble dynamics in confined liquids. The additional increase in pressure during bubble oscillations can significantly compress the bubble dynamics, resulting in a reduction in the bubble size and oscillation time. However, to the best of our knowledge, there is a lack of studies on the influence of confinement-related parameters on confined bubble dynamics and the accompanying pressure changes in liquids, as well as the change in the relationship between bubble size and oscillation time. Therefore, in this study, based on the confined Rayleigh?Plesset model, we numerically investigate the laser bubble dynamics in a spherical confined geometry. Here, the effects of the liquid size and degree of confinement on the bubble dynamics, especially on the cut-off period, are mainly studied.
A simple physical model was constructed assuming that a laser-induced spherical bubble was formed at the center of a fully sealed spherical geometry with a rigid boundary. Bubble oscillation squeezes the liquid and reduces the liquid volume, leading to pressure increase in the liquid. The relationship between the pressure increase in the liquid?solid boundary and the reduced liquid volume was assumed to be linear and linked to the bulk modulus of the liquid. The compressibility effects of the liquid were neglected, and the degree of confinement was assumed to be constant. Based on these results, a confined Rayleigh?Plesset equation was derived by introducing the confinement effect into the Rayleigh model. For the laser-induced bubbles, the ratio of the equilibrium radius to the initial radius was set at a constant value of 10.4. The radius?time curves for various bubble sizes were obtained by tuning the initial bubble radius. Using this confined Rayleigh?Plesset equation, the influence of liquid size and confinement degree on bubble dynamics was investigated.
For a laser-induced spherical bubble with Rayleigh size of 300 μm in the fully confined spherical geometry with a radius of 3 mm, the bubble size and oscillation period are highly reduced (Fig.2). The oscillation period is more vulnerable to confinement than the bubble size [Fig.3 (a)]. With increasing bubble size, the oscillation period first increases and then decreases, reaching a maximum value of 15.3 μs when the bubble size increases to 154.1 μm (corresponding to a Rayleigh radius of 209.9 μm and a Rayleigh time of 39.1 μs) [Fig.3 (b)]. The maximum period that a bubble reaches in a confined liquid is called the cut-off period. Figure 5 shows the bubble dynamics in a fully confined liquid with different liquid sizes. It shows that the cut-off period is linearly related to the corresponding maximum radius, with a coefficient of 0.1 s/m, which still holds under various degrees of confinement. Moreover, it is found that the cut-off period is reached in the fully confined condition when the Rayleigh radius is 0.06 times the liquid radius. When the cut-off period is reached, the maximum bubble size is 0.05 times the liquid radius. We also demonstrate the effects of the confinement degree on the bubble dynamics and show that the cutoff period rapidly decreases with increasing confinement degree (Fig.6).
In this study, based on the confined Rayleigh?Plesset model, we simulate the laser-induced spherical bubble dynamics in a spherical confined geometry with different liquid sizes and confinements. Owing to the prominent additional pressure increase in the liquid during the bubble oscillations, the bubble dynamics are remarkably compressed with a reduced oscillation period and maximum bubble radius, and the oscillation period is more vulnerable to confinement than the bubble radius. The confinement effect leads to a cut-off period linearly related to the corresponding maximum bubble size. It is strongly affected by the liquid size and degree of confinement. This study provides a better understanding of the principles of cardiovascular laser plaque treatment.
.- Publication Date: Jan. 13, 2025
- Vol. 52, Issue 3, 0307208 (2025)
With the rapid advancement of quantum technology, broadband entangled photon sources have emerged as promising tools for a variety of applications, including quantum communications, precision measurements, spectroscopy, and quantum computation. However, current methods for generating broadband entangled photons face challenges, particularly in achieving frequencies over 100 THz. To address these limitations, this study proposes a coupled waveguide system based on a silicon on insulator (SOI) platform that utilizes evanescent-wave coupling phase matching (ECPM) to generate a flat ultra-wideband spectrum covering 114 THz and produces photons with a photon flux density of up to 1.11 ns-1·THz-1 when pumped with a power of 100 mW. Furthermore, the analysis results of the dual photon wave function and entanglement entropy confirm that the generated photon pairs exhibit high-quality continuous frequency entanglement characteristics. This study aims to provide an efficient and cost-effective solution for broadband entangled photon sources in applications such as wavelength-division multiplexing (WDM) systems, quantum optical coherence tomography, spectroscopic measurements, and quantum communications.
The study uses theoretical analysis and numerical calculation methods. Initially, the research focuses on observing the ultra-broadband phase matching phenomenon in a coupled waveguide system via the calculation of the phase matching function. Subsequently, investigations are conducted on four-wave mixing (FWM) with different mode combinations to select an appropriate mode combination. The study then quantifies the bandwidth of phase matching and optimizes the structural parameters of the waveguide in a three-dimensional solution space by using a simulated annealing algorithm. Finally, numerical calculations are performed to determine the photon flux density, two-photon wave function, and entanglement entropy of the photons generated by the designed waveguide. The results confirm that the designed structure efficiently and uniformly generates ultra-wideband continuously entangled photons.
After optimization, the ultra-broadband continuous entanglement source achieves a bandwidth exceeding 100 THz (Fig. 4). Specifically, with a pump power of 100 mW and propagation distance of 3 mm, the FWM exhibits a maximum efficiency of -40.8 dB, which corresponds to a frequency bandwidth of 114 THz at 5 dB (Fig. 5). The results of a sensitivity analysis indicate that maintaining an equivalent bandwidth above 700 nm is feasible by varying the coupling gap within the range of 370 nm to 390 nm, waveguide width within 764 nm to 756 nm, and waveguide height within 327 nm to 334 nm. It is further shown that the designed broadband entangled photon source can achieve a bandwidth exceeding 700 nm within an allowable error range (Fig. 6). Numerical calculations demonstrate that the generated photons exhibit high-quality continuous frequency entanglement and frequency dependence with an entanglement entropy of 7.211 for broadband entangled photons and that the maximum photon flux density reaches 1.11 ns-1·THz-1 at a pump power of 100 mW (Fig. 7). Overall, the results indicate that the proposed structure not only enables the generation of ultra-broadband entangled photons but also achieves high conversion efficiency (Table 1).
This study proposes a method by which to generate broadband entangled photons in a coupled waveguide system using ECPM. Compared with previous work, we generate entangled photons with a wider bandwidth and maintain a high generation efficiency by optimizing the structure of the coupled waveguide. The simple structure of the device significantly reduces the processing difficulty. First, we discover the mechanism of ultra-broadband phase matching in the coupled waveguide. Second, we quantify the contribution of phase matching to the bandwidth of FWM generation and optimize the waveguide geometry by using a simulated annealing algorithm to achieve ultra-broadband phase matching. Compared with that observed before the optimization, the phase matching bandwidth of the designed waveguide structure is expanded by 5.45 times. In addition, the results of this study demonstrate that the generated photons have a high level of continuous-frequency entanglement properties via the calculation of the two-photon wave function and entanglement entropy. The waveguide system designed and optimized in this study can generate broadband entangled photons spanning the O, E, S, C, L, and U bands in the wavelength range of 1184 nm to 2158 nm with a bandwidth as high as 114 THz. In addition, the structure produces photons with a photon flux density of up to 1.11 ns-1·THz-1 at a pump power of 100 mW while guaranteeing the bandwidth and spectral flatness. Finally, the scheme proposed in this study for the generation of broadband entangled photons is also applicable to waveguide systems of other materials. Hence, these findings broaden the application range of the ECPM in the field of future broadband entangled photon sources.
.- Publication Date: Jan. 10, 2025
- Vol. 52, Issue 3, 0312001 (2025)
- Publication Date: Jan. 09, 2025
- Vol. 52, Issue 3, 0316001 (2025)
- Publication Date: Jan. 20, 2025
- Vol. 52, Issue 3, 0316002 (2025)