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ConResNet

This repo holds the pytorch implementation of ConResNet:

Paper: Inter-slice Context Residual Learning for 3D Medical Image Segmentation. (https://ieeexplore.ieee.org/abstract/document/9245569) (https://arxiv.org/pdf/2011.14155.pdf)

Requirements

Python 3.6
Torch==1.4.0
Apex==0.1

Usage

0. Installation

  • Clone this repo
git clone https://github.com/jianpengz/ConResNet.git
cd ConResNet

1. Data Preparation

  • Put the data and image_id_list in dataset/.

2. Training

  • Run run.sh to start the training.

3. Evaluation

  • Run python test.py to start the evaluation.

7. Citation

If this code is helpful for your study, please cite:

@article{zhang2020conresnet,
  title={Inter-slice Context Residual Learning for 3D Medical Image Segmentation},
  author={Zhang, Jianpeng and Xie, Yutong and Wang, Yan and Xia, Yong},
  journal={IEEE Transactions on Medical Imaging},
  volume={40},
  number={2},
  pages={661-672},
  year={2021},
  publisher={IEEE}
}

Contact

Jianpeng Zhang (james.zhang@mail.nwpu.edu.cn)

About

[IEEE-TMI2020] Inter-slice Context Residual Learning for 3D Medical Image Segmentation

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