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OpenMMLab Detection Toolbox and Benchmark

deep learning for image processing including classification and object-detection etc.

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

Image augmentation for machine learning experiments.

Mamba SSM architecture

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Image augmentation for object detection, segmentation and classification

Mamba-UNet Zoo

code for MICCAI 2019 paper 'Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation'.

How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study

This is the official code repository for "MedMamba: Vision Mamba for Medical Image Classification"

A PyTorch framework for medical image segmentation

Official Code for *Mixed Transformer UNet for Medical Image Segmentation*

Official Code for our MedIA paper "Mutual Consistency Learning for Semi-supervised Medical Image Segmentation" (ESI Highly Cited Paper)

NeurIPS 2023: Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation

[BMVC2023] Spatial and Planar Consistency for Semi-Supervised Volumetric Medical Image Segmentation

pytorch implementation for The Fully Convolutional Transformer(FCT)

2018 Left Atrium Segmentation (MRI)

[PRCV 2021] The official code for "Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation"

[ISBI 2024] Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive Learning

[CMIG‘2022] [Pytorch]A Contrastive Consistency Semi-supervised Left Atrium Segmentation Model

Semi-Supervised-Learning

Official PyTorch implementation of the paper: <Bootstrap Representation Learning for Segmentation on Medical Volumes and Sequences>