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Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation

Introduction

This repository contains the PyTorch implementation of:

Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation, ISBI 2022.

test1

Requirements

Usage

1.Folder Structure

We except the data folder has these structures:

root/    
|-- data/
    |-- ISIC/
    |   |-- TrainDataset/
    |   |   |-- images/
    |   |   |   |-- ISIC_0000001.jpg 
    |   |   |   |-- ISIC_0000002.jpg 
    |   |   |   ...
    |   |   |-- masks/
    |   |       |-- ISIC_0000001.jpg 
    |   |       |-- ISIC_0000002.jpg 
    |   |       ...
    |   |-- ValidationDataset/
    |   |   |-- images/
    |   |   |   |-- ISIC_0000003.jpg 
    |   |   |   |-- ISIC_0000004.jpg 
    |   |   |   ...
    |   |   |-- masks/
    |   |       |-- ISIC_0000003.jpg 
    |   |       |-- ISIC_0000004.jpg 
    |   |       ...
    |   |-- TestDataset/
    |       |-- images/
    |       |   |-- ISIC_0000005.jpg 
    |       |   |-- ISIC_0000006.jpg 
    |       |   ...
    |       |-- masks/
    |           |-- ISIC_0000005.jpg 
    |           |-- ISIC_0000006.jpg 
    |           ...
    |-- Kvasir-SEG/
        |-- TrainDataset/
        |   |-- images/
        |   |   ...
        |   |-- masks/
        |       ...
        |-- ValidationDataset/
        |   |-- images/
        |   |   ...
        |   |-- masks/
        |       ...
        |-- TestDataset/
            |-- images/
            |   ...
            |-- masks/
                ...

2. Training

python main.py --config ./expconfigs/XXX.yaml

3. Testing

python main.py --config ./expconfigs/XXX.yaml --test

Citation

If you feel this work is helpful, please cite our paper

@inproceedings{zhao2022cross,
  title={Cross-Level Contrastive Learning and Consistency Constraint for Semi-Supervised Medical Image Segmentation},
  author={Zhao, Xinkai and Fang, Chaowei and Fan, De-Jun and Lin, Xutao and Gao, Feng and Li, Guanbin},
  booktitle={2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)},
  pages={1--5},
  year={2022},
  organization={IEEE}
}