PyTorch bindings for PYRONN）（2004年）。https://github.com/csyben/PYRONN）
pyronn-torch的Python项目详细描述
派伦火炬
此存储库为PYRO-NN提供PyTorch绑定， 用于CT重建的反向传播投影仪的集合。在
请随意引用我们的出版物：
@article{PYRONN2019,author={Syben, Christopher and Michen, Markus and Stimpel, Bernhard and Seitz, Stephan and Ploner, Stefan and Maier, Andreas K.},title={Technical Note: PYRO-NN: Python reconstruction operators in neural networks},year={2019},journal={Medical Physics},}
安装
来自PyPI：
^{pr2}$从该存储库：
git clone --recurse-submodules --recursive https://github.com/theHamsta/pyronn-torch.git
cd pyronn-torch
pip install torch
pip install -e .
您可以使用
python setup.py bdist_wheel
用法
importpyronn_torch#ConeBeamProjector(volume_shape,# volume_spacing,# volume_origin,# projection_shape,# projection_spacing,# projection_origin,# projection_matrices)projector=pyronn_torch.ConeBeamProjector((128,128,128),(2.0,2.0,2.0),(-127.5,-127.5,-127.5),(2,480,620),[1.0,1.0],(0,0),np.array([[[-3.10e+2,-1.20e+03,0.00e+00,1.86e+5],[-2.40e+2,0.00e+00,1.20e+03,1.44e+5],[-1.00e+00,0.00e+00,0.00e+00,6.00e+2]],[[-2.89009888e+2,-1.20522754e+3,-1.02473585e-13,1.86000000e+5],[-2.39963440e+2,-4.18857765e+0,1.20000000e+3,1.44000000e+5],[-9.99847710e-01,-1.74524058e-2,0.00000000e+0,6.00000000e+2]]])# two projection matrices)projection=projector.new_projection_tensor(requires_grad=True)projection+=1.result=projector.project_backward(projection,use_texture=True)assertprojection.requires_gradassertresult.requires_gradloss=result.mean()loss.backward()
或者使用PyCONRAD（pip install pyconrad）更简单
projector=pyronn_torch.ConeBeamProjector.from_conrad_config()
然后可以使用CONRAD完成配置 （从命令行使用conrad启动）
- 项目
标签：
欢迎加入QQ群-->： 979659372
