Pytorch Medical Segmentation
This repository is an unoffical PyTorch implementation of Medical segmentation in 3D and 2D.
- You can modify hparam.py to determine whether 2D or 3D segmentation and whether multicategorization is possible.
- We provide algorithms for almost all 2D and 3D segmentation.
- This repository is compatible with almost all medical data formats(e.g. nii.gz, nii, mhd, nrrd, ...), by modifying fold_arch in hparam.py of the config.
- without pretrained-model
set hparam.train_or_test to 'train' python main.py
- with pretrained-model
set hparam.train_or_test to 'train' python main.py -k True
set hparam.train_or_test to 'test' python main.py
- [x] unet
- [x] unet++
- [x] miniseg
- [x] segnet
- [x] pspnet
- [x] highresnet(copy from https://github.com/fepegar/highresnet, Thank you to fepegar for your generosity!)
- [x] deeplab
- [x] fcn
- [x] unet3d
- [x] densevoxelnet3d
- [x] fcn3d
- [x] vnet3d
- [x] highresnert(copy from https://github.com/fepegar/highresnet, Thank you to fepegar for your generosity!)
- [x] densenet3d
- [ ] dataset
- [ ] benchmark
- [ ] nnunet
By The Way
This project is not perfect and there are still many problems. If you are using this project and would like to give the author some feedbacks, you can send Kangneng Zhou an email.