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

Overview

Semi-supervised-learning-for-medical-image-segmentation.

  • Recently, semi-supervised image segmentation has become a hot topic in medical image computing, unfortunately, there are only a few open-source codes and datasets, since the privacy policy and others. For easy evaluation and fair comparison, we are trying to build a semi-supervised medical image segmentation benchmark to boost the semi-supervised learning research in the medical image computing community. If you are interested, you can push your implementations or ideas to this repository at any time.

  • This project was originally developed for our previous works (DTC and URPC), if you find it's useful for your research, please cite the followings:

      @InProceedings{luo2021urpc,
      author={Luo, Xiangde and Liao, Wenjun and Chen, Jieneng and Song, Tao and Chen, Yinan and Zhang, Shichuan and Chen, Nianyong and Wang, Guotai and Zhang, Shaoting},
      title={Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency},
      booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2021},
      year={2021},
      pages={318--329}
      }
    
      @article{luo2021semi,
        title={Semi-supervised Medical Image Segmentation through Dual-task Consistency},
        author={Luo, Xiangde and Chen, Jieneng and Song, Tao and  Wang, Guotai},
        journal={AAAI Conference on Artificial Intelligence},
        year={2021},
        pages={8801-8809}
      }
      @misc{ssl4mis2020,
        title={{SSL4MIS}},
        author={Luo, Xiangde and Chen, Jieneng and Song, Tao and  Wang, Guotai},
        howpublished={\url{https://github.com/HiLab-git/SSL4MIS}},
        year={2020}
      }
    

Literature reviews of semi-supervised learning approach for medical image segmentation (SSL4MIS).

Date The First and Last Authors Title Code Reference
2021-09 K. Wang and Y. Wang Tripled-Uncertainty Guided Mean Teacher Model for Semi-supervised Medical Image Segmentation Code MICCAI2021
2021-09 H. Huang and R. Tong 3D Graph-S2Net: Shape-Aware Self-ensembling Network for Semi-supervised Segmentation with Bilateral Graph Convolution None MICCAI2021
2021-09 L. Zhu and B. Ooi Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation Code MICCAI2021
2021-09 R. Zhang and G. Li Self-supervised Correction Learning for Semi-supervised Biomedical Image Segmentation Code MICCAI2021
2021-09 D. Kiyasseh and A. Chen Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning None MICCAI2021
2021-09 Y. Wu and J. Cai Enforcing Mutual Consistency of Hard Regions for Semi-supervised Medical Image Segmentation None Arxiv
2021-09 X. Zeng and Y. Wang Reciprocal Learning for Semi-supervised Segmentation Code MICCAI2021
2021-09 G. Zhang and S. Jiang Automatic segmentation of organs at risk and tumors in CT images of lung cancer from partially labelled datasets with a semi-supervised conditional nnU-Net None CMPB2021
2021-09 J. Chen and G. Yang Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data Code TMI2021
2021-09 X. Hu and Y. Shi Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation Code MICCAI2021
2021-09 G. Chen and J. Shi MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation Code NeuroImage2021
2021-08 H. Peiris and M. Harandi Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation Code MICCAI2021
2021-08 J. Sun and Y. Kong Semi-Supervised Medical Image Semantic Segmentation with Multi-scale Graph Cut Loss None ICIP2021
2021-08 X. Shen and J. Lu PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning None ArXiv
2021-08 C. You and J. Duncan SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation None Arxiv
2021-08 C. Li and P. Heng Self-Ensembling Co-Training Framework for Semi-supervised COVID-19 CT Segmentation None JBHI2021
2021-08 H. Yang and P. H. N. With Medical Instrument Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning None JBHI2021
2021-07 W. Ding and H. Hawash RCTE: A Reliable and Consistent Temporal-ensembling Framework for Semi-supervised Segmentation of COVID-19 Lesions None Information Fusion2021
2021-06 X. Liu and S. A. Tsaftaris Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation Code MICCAI2021
2021-06 P. Pandey and Mausam Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation None MICCAI2021
2021-06 C. Li and Y. Yu Hierarchical Deep Network with Uncertainty-aware Semi-supervised Learning for Vessel Segmentation None Arxiv
2021-05 J. Xiang and S. Zhang Self-Ensembling Contrastive Learning for Semi-Supervised Medical Image Segmentation None Arxiv
2021-05 S. Li and C. Guan Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation None Arxiv
2021-05 C. You and J. Duncan Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation None Arxiv
2021-05 Z. Xie and J. Yang Semi-Supervised Skin Lesion Segmentation with Learning Model Confidence None ICASSP2021
2021-04 S. Reiß and R. Stiefelhagen Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation None CVPR2021
2021-04 S. Chatterjee and A. Nurnberger DS6, Deformation-aware Semi-supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data Code MIDL
2021-04 A. Meyer and M. Rak Uncertainty-Aware Temporal Self-Learning (UATS): Semi-Supervised Learning for Segmentation of Prostate Zones and Beyond Code Arxiv
2021-04 Y. Li and P. Heng Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images None MICCAI2021
2021-03 Y. Zhang and C. Zhang Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation Code PRCV2021
2021-03 J. Peng and C. Desrosiers Boosting Semi-supervised Image Segmentation with Global and Local Mutual Information Regularization Code MELBA
2021-03 Y. Wu and L. Zhang Semi-supervised Left Atrium Segmentation with Mutual Consistency Training None MICCAI2021
2021-02 J. Peng and Y. Wang Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models None Arxiv
2021-02 J. Dolz and I. B. Ayed Teach me to segment with mixed supervision: Confident students become masters Code IPMI2021
2021-02 C. Cabrera and K. McGuinness Semi-supervised Segmentation of Cardiac MRI using Image Registration None Under review for MIDL2021
2021-02 Y. Wang and A. Yuille Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction None TMI2021
2021-02 R. Alizadehsaniand U R. Acharya Uncertainty-Aware Semi-supervised Method using Large Unlabelled and Limited Labeled COVID-19 Data None Arxiv
2021-02 D. Yang and D. Xu Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan None MedIA2021
2020-01 E. Takaya and S. Kurihara Sequential Semi-supervised Segmentation for Serial Electron Microscopy Image with Small Number of Labels Code Journal of Neuroscience Methods
2021-01 Y. Zhang and Z. He Semi-supervised Cardiac Image Segmentation via Label Propagation and Style Transfer None Arxiv
2020-12 H. Wang and D. Chen Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation None Arxiv
2020-12 X. Luo and S. Zhang Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency Code MICCAI2021
2020-12 M. Abdel‐Basset and M. Ryan FSS-2019-nCov: A Deep Learning Architecture for Semi-supervised Few-Shot Segmentation of COVID-19 Infection None Knowledge-Based Systems2020
2020-11 N. Horlava and N. Scherf A comparative study of semi- and self-supervised semantic segmentation of biomedical microscopy data None Arxiv
2020-11 P. Wang and C. Desrosiers Self-paced and self-consistent co-training for semi-supervised image segmentation None MedIA2021
2020-10 Y. Sun and L. Wang Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation None MLMI2020
2020-10 L. Chen and D. Merhof Semi-supervised Instance Segmentation with a Learned Shape Prior Code LABELS2020
2020-10 S. Shailja and B.S. Manjunath Semi supervised segmentation and graph-based tracking of 3D nuclei in time-lapse microscopy Code Arxiv
2020-10 L. Sun and Y. Yu A Teacher-Student Framework for Semi-supervised Medical Image Segmentation From Mixed Supervision None Arxiv
2020-10 J. Ma and X. Yang Active Contour Regularized Semi-supervised Learning for COVID-19 CT Infection Segmentation with Limited Annotations Code Physics in Medicine & Biology2020
2020-10 W. Hang and J. Qin Local and Global Structure-Aware Entropy Regularized Mean Teacher Model for 3D Left Atrium Segmentation Code MICCAI2020
2020-10 K. Tan and J. Duncan A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography None MICCAI2020
2020-10 Y. Wang and Z. He Double-Uncertainty Weighted Method for Semi-supervised Learning None MICCAI2020
2020-10 K. Fang and W. Li DMNet: Difference Minimization Network for Semi-supervised Segmentation in Medical Images None MICCAI2020
2020-10 X. Cao and L. Cheng Uncertainty Aware Temporal-Ensembling Model for Semi-supervised ABUS Mass Segmentation None TMI2020
2020-09 Z. Zhang and W. Zhang Semi-supervised Semantic Segmentation of Organs at Risk on 3D Pelvic CT Images None Arxiv
2020-09 J. Wang and G. Xie Semi-supervised Active Learning for Instance Segmentation via Scoring Predictions None BMVC2020
2020-09 X. Luo and S. Zhang Semi-supervised Medical Image Segmentation through Dual-task Consistency Code AAAI2021
2020-08 X. Huo and Q. Tian ATSO: Asynchronous Teacher-Student Optimization for Semi-Supervised Medical Image Segmentation None Arxiv
2020-08 Y. Xie and Y. Xia Pairwise Relation Learning for Semi-supervised Gland Segmentation None MICCAI2020
2020-07 K. Chaitanya and E. Konukoglu Semi-supervised Task-driven Data Augmentation for Medical Image Segmentation Code Arxiv
2020-07 S. Li and X. He Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images Code MICCAI2020
2020-07 Y. Li and Y. Zheng Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-Supervised Medical Image Segmentation None MICCAI2020
2020-07 Z. Zhao and P. Heng Learning Motion Flows for Semi-supervised Instrument Segmentation from Robotic Surgical Video Code MICCAI2020
2020-07 Y. Zhou and P. Heng Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation Code MICCAI2020
2020-07 A. Tehrani and H. Rivaz Semi-Supervised Training of Optical Flow Convolutional Neural Networks in Ultrasound Elastography None MICCAI2020
2020-07 Y. He and S. Li Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation None MedIA2020
2020-07 J. Peng and C. Desrosiers Mutual information deep regularization for semi-supervised segmentation Code MIDL2020
2020-07 Y. Xia and H. Roth Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation None WACV2020,MedIA2020
2020-07 X. Li and P. Heng Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation Code TNNLS2020
2020-06 F. Garcıa and S. Ourselin Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised Learning None MICCAI2020
2020-06 H. Yang and P. With Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet None MICCAI2020
2020-05 G. Fotedar and X. Ding Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts None MICCAI2020
2020-04 C. Liu and C. Ye Semi-Supervised Brain Lesion Segmentation Using Training Images with and Without Lesions None ISBI2020
2020-04 R. Li and D. Auer A Generic Ensemble Based Deep Convolutional Neural Network for Semi-Supervised Medical Image Segmentation Code ISBI2020
2020-04 K. Ta and J. Duncan A Semi-Supervised Joint Learning Approach to Left Ventricular Segmentation and Motion Tracking in Echocardiography None ISBI2020
2020-04 Q. Chang and D. Metaxas Soft-Label Guided Semi-Supervised Learning for Bi-Ventricle Segmentation in Cardiac Cine MRI None ISBI2020
2020-04 D. Fan and L. Shao Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Images Code TMI2020
2019-10 L. Yu and P. Heng Uncertainty-aware self-ensembling model for semi-supervised 3D left atrium segmentation Code MICCAI2019
2019-10 G. Bortsova and M. Bruijne Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations None MICCAI2019
2019-10 Y. He and S. Li DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy None MICCAI2019
2019-10 H. Zheng and X. Han Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior None MICCAI2019
2019-10 P. Ganayea and H. Cattin Removing Segmentation Inconsistencies with Semi-Supervised Non-Adjacency Constraint Code MedIA2019
2019-10 Y. Zhao and C. Liu Multi-view Semi-supervised 3D Whole Brain Segmentation with a Self-ensemble Network None MICCAI2019
2019-10 H. Kervade and I. Ayed Curriculum semi-supervised segmentation None MICCAI2019
2019-10 S. Chen and M. Bruijne Multi-task Attention-based Semi-supervised Learning for Medical Image Segmentation None MICCAI2019
2019-10 Z. Xu and M. Niethammer DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation None MICCAI2019
2019-10 S. Sedai and R. Garnavi Uncertainty Guided Semi-supervised Segmentation of Retinal Layers in OCT Images None MICCAI2019
2019-10 G. Pombo and P. Nachev Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning Code MICCAI2019
2019-06 W. Cui and C. Ye Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model None IPMI2019
2019-06 K. Chaitanya and E. Konukoglu Semi-supervised and Task-Driven Data Augmentation Code IPMI2019
2019-04 M. Jafari and P. Abolmaesumi Semi-Supervised Learning For Cardiac Left Ventricle Segmentation Using Conditional Deep Generative Models as Prior None ISBI2019
2019-03 Z. Zhao and Z. Zeng Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation None BHI
2019-03 J. Peng and C. Desrosiers Deep co-training for semi-supervised image segmentation Code PR2020
2019-01 Y. Zhou and A. Yuille Semi-Supervised 3D Abdominal Multi-Organ Segmentation via Deep Multi-Planar Co-Training None WACV2019
2018-10 P. Ganaye and H. Cattin Semi-supervised Learning for Segmentation Under Semantic Constraint Code MICCAI2018
2018-10 A. Chartsias and S. Tsaftari Factorised spatial representation learning: application in semi-supervised myocardial segmentation None MICCAI2018
2018-09 X. Li and P. Heng Semi-supervised Skin Lesion Segmentation via Transformation Consistent Self-ensembling Model Code BMVC2018
2018-04 Z. Feng and D. Shen Semi-supervised learning for pelvic MR image segmentation based on multi-task residual fully convolutional networks None ISBI2018
2017-09 L. Gu and S. Aiso Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels) None MICCAI2017
2017-09 S. Sedai and R. Garnavi Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoder None MICCAI2017
2017-09 W. Bai and D. Rueckert Semi-supervised Learning for Network-Based Cardiac MR Image Segmentation None MICCAI2017

Code for semi-supervised medical image segmentation.

Some implementations of semi-supervised learning methods can be found in this Link.

Conclusion

  • This repository provides daily-update literature reviews, algorithms' implementation, and some examples of using PyTorch for semi-supervised medical image segmentation. The project is under development. Currently, it supports 2D and 3D semi-supervised image segmentation and includes five widely-used algorithms' implementations.

  • In the next two or three months, we will provide more algorithms' implementations, examples, and pre-trained models.

Questions and Suggestions

  • If you have any questions or suggestions about this project, please contact me through email: [email protected] or QQ Group (Chinese):906808850.
Owner
Healthcare Intelligence Laboratory
Healthcare Intelligence Laboratory
A Quick and Dirty Progressive Neural Network written in TensorFlow.

prog_nn .▄▄ · ▄· ▄▌ ▐ ▄ ▄▄▄· ▐ ▄ ▐█ ▀. ▐█▪██▌•█▌▐█▐█ ▄█▪ •█▌▐█ ▄▀▀▀█▄▐█▌▐█▪▐█▐▐▌ ██▀

SynPon 53 Dec 12, 2022
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra

VITA 77 Oct 05, 2022
Utilizes Pose Estimation to offer sprinters cues based on an image of their running form.

Running-Form-Correction Utilizes Pose Estimation to offer sprinters cues based on an image of their running form. How to Run Dependencies You will nee

3 Nov 08, 2022
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer

Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer Paper on arXiv Public PyTorch implementation of two-stage peer-reg

NNAISENSE 38 Oct 14, 2022
Code for Deep Single-image Portrait Image Relighting

Deep Single-Image Portrait Relighting [Project Page] Hao Zhou, Sunil Hadap, Kalyan Sunkavalli, David W. Jacobs. In ICCV, 2019 Overview Test script for

438 Jan 05, 2023
Educational API for 3D Vision using pose to control carton.

Educational API for 3D Vision using pose to control carton.

41 Jul 10, 2022
FANet - Real-time Semantic Segmentation with Fast Attention

FANet Real-time Semantic Segmentation with Fast Attention Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko , Stan Sc

Ping Hu 42 Nov 30, 2022
A Light CNN for Deep Face Representation with Noisy Labels

A Light CNN for Deep Face Representation with Noisy Labels Citation If you use our models, please cite the following paper: @article{wulight, title=

Alfred Xiang Wu 715 Nov 05, 2022
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

Yue Yu 58 Dec 21, 2022
MMFlow is an open source optical flow toolbox based on PyTorch

Documentation: https://mmflow.readthedocs.io/ Introduction English | 简体中文 MMFlow is an open source optical flow toolbox based on PyTorch. It is a part

OpenMMLab 688 Jan 06, 2023
CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped

CSWin-Transformer This repo is the official implementation of "CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows". Th

Microsoft 409 Jan 06, 2023
YOLOv5 in PyTorch > ONNX > CoreML > TFLite

This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and e

Ultralytics 34.1k Dec 31, 2022
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

Yaping Zhao 19 Nov 05, 2022
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"

SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

60 Dec 22, 2022
Spatiotemporal resampling methods for mlr3

mlr3spatiotempcv Package website: release | dev Spatiotemporal resampling methods for mlr3. This package extends the mlr3 package framework with spati

45 Nov 21, 2022
Visual dialog agents with pre-trained vision-and-language encoders.

Learning Better Visual Dialog Agents with Pretrained Visual-Linguistic Representation Or READ-UP: Referring Expression Agent Dialog with Unified Pretr

7 Oct 08, 2022
Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22)

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

Shigang Li 9 Oct 29, 2022
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences [CVPR2021]

Patch2Pix for Accurate Image Correspondence Estimation This repository contains the Pytorch implementation of our paper accepted at CVPR2021: Patch2Pi

Qunjie Zhou 199 Nov 29, 2022
Poisson Surface Reconstruction for LiDAR Odometry and Mapping

Poisson Surface Reconstruction for LiDAR Odometry and Mapping Surfels TSDF Our Approach Table: Qualitative comparison between the different mapping te

Photogrammetry & Robotics Bonn 305 Dec 21, 2022
Food recognition model using convolutional neural network & computer vision

Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper

Hemanth Chandran 1 Jan 13, 2022