BHPC

KO | EN

gitlite — search

#javascript #python #hacktoberfest #react #ai #typescript #llm #go #golang #android #machine-learning #rust #deep-learning #linux

(★ 12)

Codes about our paper "Semi-supervised medical image segmentation via hard positives oriented contrastive learning"

BHPC Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Semi-supervised Medical Image Segmentation via Hard Positives oriented Contrastive Learning
This is the pytorch implementation of paper "Semi-supervised Medical Image Segmentation via Hard Positives oriented Contrastive Learning".

![workflow of our methods](https://raw.githubusercontent.com/PerPerZXY/BHPC/main/Overview.png)

Email addresses: tangcheng1@stu.scu.edu.cn & perperstudy@gmail.com (Joint First Authors) & wangyanscu@hotmail.com (Corresponding Author)

## Setup
### Environment
```
python=3.7.10
torch==1.8.1
torchvision=0.9.1
```
### Dataset
We will take the [Hippocampus dataset](https://drive.google.com/file/d/1RzPB1_bqzQhlWvU-YGvZzhx2omcDh38C/view?usp=sharing) as the example to illustrate how to do the preprocessing. Put the images .nii.gz files in ./data/Hippocampus/imgs folder and labels files in ./data/Hippocampus/labels.
```
cd dataset/prepare_dataset
python preprcocessing.py
python create_splits.py
```

Afterwards, the images and their respective labels will be combined and saved in a .npy file. The shape of the images will be normalized to match the target size.

## Run the codes
To run the Stage I: Unsupervised Image-level Contrastive Learning,
```
bash run_simclr.sh
```
To run the Stage II: Supervised Pixel-level Contrastive Learning,
```
bash run_coseg.sh
```
To combine the above two pretraining, run run_simclr.sh first and the pretrained model will be saved at save/simclr/Hippocampus/ and set --pretrained_model_path  ${the saved model path} in run_coseg.sh. Remember to load the saved pre-trained model.

To run the Stage III: (Semi-supervised Segmentation),
```
bash run_seg.sh
```

## Important Notes
* In all of the aforementioned three files, "train_sample" denotes the percentage of labeled data to be utilized.

BHPC

BHPC Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

BHPC

BHPC Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README