https://github.com/MQinghe/MiDSS

https://github.com/MQinghe/MiDSS

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• Host: GitHub
• URL: https://github.com/MQinghe/MiDSS
• Owner: MQinghe
• Created: 2024-03-15T08:07:44.000Z (8 months ago)
• Default Branch: master
• Last Pushed: 2024-04-08T13:16:27.000Z (7 months ago)
• Last Synced: 2024-04-08T14:33:20.531Z (7 months ago)
• Language: Python
• Size: 15.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# MiDSS

### 1. Introduction

This repository contains the implementation of the paper **Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation**

### 2. Dataset Construction

The dataset needs to be divided into two folders for training and testing. The training and testing data should be in the format of the "data" folder.

### 3. Train

`code/train.py` is the implementation of our method on the Prostate and Fundus dataset.

`code/train_MNMS.py` is the implementation of our method on the M&Ms dataset.

Modify the paths in lines 631 to 636 of the code.

```python

if args.dataset == 'fundus':

    train_data_path='../../data/Fundus' # the folder of fundus dataset

elif args.dataset == 'prostate':

    train_data_path="../../data/ProstateSlice" # the folder of prostate dataset

elif args.dataset == 'MNMS':

    train_data_path="../../data/MNMS/mnms" # the folder of mnms dataset

```

then simply run:

```python

python train.py --dataset ... --lb_domain ... --lb_num ... --save_name ... --gpu 0

```

### 4. Test

To run the evaluation code, please update the path of the dataset in `test.py`:

Modify the paths in lines 249 to 254 of the code.

then simply run:

```

python test.py --dataset ... --save_name ... --gpu 0

```

### 5. Acknowledgement

This project is based on the code from the [SSL4MIS](https://github.com/HiLab-git/SSL4MIS) project.

Thanks a lot for their great works.