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
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