Yu Zhang, Haoran Li, Cheng Li, Fei Li, Shanshan Wang. Combinatorial Reconstruction and Segmentation of Magnetic Resonance Image Using Teacher Forcing[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415024
- Laser & Optoelectronics Progress
- Vol. 59, Issue 14, 1415024 (2022)
Fig. 1. Framework of the proposed multi-task MRI method
Fig. 2. The proposed improved teacher forcing scheme (TFS)
Fig. 3. Examples of 1D random K-space mask with different acceleration factors. (a) Mask under 4× acceleration; (b) mask under 8× acceleration
Fig. 4. Examples of lesion segmentation results and image reconstruction error maps of samples on the ATLAS dataset (acceleration factor is 4), from left to right is annotation, ours, SegNetMRI, U-Net (top) and D5C5 (bottom), SynNet, LI-Net, SERANet
Fig. 5. Violin-plot of the segmentation results on the ATLAS dataset
Fig. 6. Boxplot of the segmentation results on the ATLAS dataset
Fig. 7. Examples of lesion segmentation results and image reconstruction error maps of samples on the in-house dataset (acceleration factor is 4), from left to right is label, ours, SegNetMRI, U-Net (top) and D5C5 (bottom)
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Table 1. Experimental results of different methods on the ATLAS dataset (acceleration factor is 4), bold letters indicate the best result
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Table 2. Experimental results of different methods on the ATLAS dataset (acceleration factor is 8)
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Table 3. Ablation study on the ATLAS dataset of effectiveness evaluation of the proposed teacher forcing scheme (acceleration factor is 4)
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Table 4. Experimental results of different methods on the in-house dataset (acceleration factor is 4)
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