A lib of CT projector and back-projector based on PyTorch
Coded with distance driven method [1, 2]
If you use the code, please cite our work
@article{xia2021magic,
title={MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction},
author={Xia, Wenjun and Lu, Zexin and Huang, Yongqiang and Shi, Zuoqiang and Liu, Yan and Chen, Hu and Chen, Yang and Zhou, Jiliu and Zhang, Yi},
journal={IEEE Transactions on Medical Imaging},
year={2021},
publisher={IEEE}
}
The following is the step-by-step instruction to install this lib using conda
Create Conda environment
conda create -n ctlib
Enter the enviroment and install pytorch
conda activate ctlib
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
Notice: Usually the cudatoolkit installed from nvidia channel will provide the complier. But if you install the previous pytorch version using earlier cudatoolkit which is not from nvidia channel, the cudatoolkit may not include the complier. The later installation will report the error that can't find nvcc. If so, you need install the lib of cudatoolkit-dev as follows:
conda install cudatoolkit-dev -c conda-forge
Move to the the directory of this lib, and then compile and install
python setup.py install
projection(image, options): Projector of CT
projection_t(projection, options): Transpose of projector
backprojection_t(image, options): Transpose of backprojector
backprojection(projection, options): Backprojector of CT
fbp(projection, options): FBP with RL filter
laplacian(input, k): Computation of adjancency matrix in [3]
image: 4D torch tensor, B x 1 x H x W,
projection: 4D torch tensor, B x 1 x V x D, V is the total number of scanning views, D is the total number of detector bins
options: 12D torch vector for fan beam and 9D torch vector for parallel beam, scanning geometry parameters, including
views: Number of scanning views
dets: Number of detector bins
width and height: Spatial resolution of images
dImg: Physical length of a pixel
dDet: Interval between two adjacent detector bins, especially, interval is rad for equal angle fan beam
Ang0: Starting angle
dAng: Interval between two adjacent scanning views: rad
s2r: The distance between x-ray source and rotation center, not needed in parallel beam
d2r: The distance between detector and roration center, not needed in parallel beam
binshift: The shift of the detector
scan_type: 0 is equal distance fan beam, 1 is euql angle fan beam and 2 is parallel beam
[1] B. De Man and S. Basu, “Distance-driven projection and backprojection,” in IEEE Nucl. Sci. Symp. Conf. Record, vol. 3, 2002, pp. 1477–80.
[2] B. De Man and S. Basu, “Distance-driven projection and backprojection in three dimensions,” Phys. Med. Biol., vol. 49, no. 11, p. 2463, 2004.
[3] Xia, W., Lu, Z., Huang, Y., Shi, Z., Liu, Y., Chen, H., ... & Zhang, Y. (2021). MAGIC: Manifold and Graph Integrative Convolutional Network for Low-Dose CT Reconstruction. IEEE Transactions on Medical Imaging.