Dose reduction becomes one of the hot research fields in the most commonly used helical computed tomography (CT) for clinical diagnostic. Local imaging using a collimator can effectively lower the CT radiation dose by reducing the direct irradiation area. Due to the limitation of the exposing area, the projection data used for local imaging reconstruction are usually truncated, resulting in local reconstruction problems. The key in local image reconstruction is how to deal with the horizontal truncation of the projection data. The helical cone beam back-projection filtration (BPF) algorithm only needs to ensure the integrity of the projections of PI line to realize the reconstruction of the entire PI line, making local reconstruction possible. Due to the complexity and irregularity of the spatial distribution of PI lines, the existing helical BPF algorithms can only realize local surface reconstruction, whereas the local volume reconstruction is difficult. For the BPF algorithm in designing the PI line and the sampling points in helical cone beam CT and the difficulty in local volume reconstruction, the tilted fan-beam back-projection filtration (TFB-BPF) reconstruction algorithm is proposed by utilizing the weighted correction and coordinate expansion, based on the circular fan beam BPF. The algorithm divides the reconstruction area into several slices, constructs the inclined fan beam geometry for each layer, and slice-by-slice reconstruction is conducted by using the weighted modified tilted fan beam BPF algorithm. The most powerful feature of the algorithm is that the filter line, equivalent to the PI line in the original helical BPF algorithm, is selected in a two-dimensional plane. Therefore, it is more concise and efficient and can be applied to the reconstruction of local volume regions. In this paper, the helical cone beam CT imaging geometry and the original helical cone beam BPF algorithm are introduced. Then, the TFB-BPF reconstruction algorithm is deduced. Experimental results show that the algorithm can effectively realize the local volume reconstruction and overall improved image quality without obvious truncation artifacts.