[AAAI 2022] Separate Contrastive Learning for Organs-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation

Last update: Dec 08, 2022

Overview

A paper

Introduction

This is an official release of the paper Separate Contrastive Learning for Organs-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation.

Separate Contrastive Learning for Organs-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation,
Jiacheng Wang, Xiaomeng Li, Yiming Han, Jing Qin, Liansheng Wang, Qichao Zhou
In: Association for the Advancement of Artificial Intelligence (AAAI), 2022
[arXiv][Bibetex]

TODO List

Complete the resources ...
Evaluate the effectiveness on more vision tasks ...

Code List

Comparison Methods, Here
Network
Pre-processing
Training Codes

Usage

First, you can download the dataset at PDDCA. To preprocess the dataset and save as ".png", run:
```
$ python utils/prepare_data.py
```
Note that some cases lack the complete annotation, so that we can obtain 32 cases with full annotation in the end.

To create the region set, alternatively run:

$ python utils/prepare_segs.py --dataset pddca --filter_method all --seg_method fb --min_size 400
$ python utils/prepare_segs.py --dataset pddca --filter_method all --seg_method slic --n_segments 32
$ python utils/prepare_segs.py --dataset pddca --filter_method all --seg_method slice --n_segments 32

Citation

If you find SepaReg useful in your research, please consider citing:

[AAAI 2022] Separate Contrastive Learning for Organs-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation

Related tags

Overview

A paper

Introduction

TODO List

Code List

Usage

Citation

Owner

Jiacheng Wang

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