A contrastive learning based semi-supervised segmentation network for medical image segmentation
A contrastive learning based semi-supervised segmentation network for medical image segmentation
This repository contains the implementation of a novel contrastive learning based semi-segmentation networks to segment the surgical tools.
Fig. 1. The architecture of Min-Max Similarity.
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The full paper is available: Min-Max Similarity
Environment
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
conda install opencv-python pillow numpy matplotlib
git clone https://github.com/AngeLouCN/Min_Max_Similarity
Data Preparation
We use three dataset to