Giter Club home page Giter Club logo

skelcon's Introduction

SkelCon

PyTorch implementation for our paper on TMI2022:

"Retinal Vessel Segmentation with Skeletal Prior and Contrastive Loss"

WebPages:

Method

Project

Project for SkelCon
    ├── code:core code for contribution in our paper
        ├── color_space_mixture.py (Data Augmentation Method)  
        ├── sample_contrastive_learning.py (Sample Contrastive Learning)  
        ├── model_skelcon.py (Skeletal Prior based Network)  
        └── ...  
    ├── docs (figures)  
        └── ... 
    ├── onnx (trained weights)  
        ├── *.onnx (Pytorch trained weights)  
        ├── infer.py (to extract vessels from fundus images with *.onnx) 
        └── ...     
    ├── proj (package for segmentation with torch)  
        ├── data (to extract datasets)  
        ├── nets (define the network)  
        ├── build.py (define the network)  
        ├── grad.py (for training)  
        ├── loop.py (for training)  
        ├── optim.py (optimizer)  
        ├── main.py   
        └── ...  
    ├── results (segmentation for fundus images on testsets)  
        ├── popular (segmentation results for popular datasets)  
        ├── generalization (segmentation results for cross-dataset-validation)  
        └── ...   

And for the training on DRIVE dataset, run the command

cd proj
python main.py --gpu=1 --db=drive

Contact

For any questions, please contact me. And my e-mails are

Citation

If you use this codes in your research, please cite the paper:

@article{tan2022retinal,
  title={Retinal Vessel Segmentation with Skeletal Prior and Contrastive Loss},
  author={Tan, Yubo and Yang, Kai-Fu and Zhao, Shi-Xuan and Li, Yong-Jie},
  journal={IEEE Transactions on Medical Imaging},
  doi={10.1109/TMI.2022.3161681},
  volume    = {41},
  number    = {9},
  pages     = {2238--2251},
  year      = {2022},
  publisher={IEEE}
}

skelcon's People

Contributors

tyb311 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

skelcon's Issues

Code question

The new codes seem to have annother question in kerasTorch object has no attribute 'val' in main.py.Looking forward to your guidance.Thanks a million.

关于对比学习的问题

您好,我最近也在做血管分割的任务。
我看你的代码中注释有不考虑负样本,只在正样本上做对比学习,且不考虑背景类。请问你是做过对比实验吗,您觉得原因是什么?以前的对比学习方案好像确实都考虑了正负样本做loss
非常感谢!!!

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.