WinterPan2017 / SSL4MIS

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

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

  • [New], We are reformatting the codebase to support the 5-fold cross-validation and randomly select labeled cases, the reformatted methods in this Branch.

  • 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 repo or contact me at any time.

  • This repo has re-implemented these semi-supervised methods (with some modifications for semi-supervised medical image segmentation, more details please refer to these original works): (1) Mean Teacher; (2) Entropy Minimization; (3) Deep Adversarial Networks; (4) Uncertainty Aware Mean Teacher; (5) Interpolation Consistency Training; (6) Uncertainty Rectified Pyramid Consistency; (7) Cross Pseudo Supervision; (8) Cross Consistency Training; (9) Deep Co-Training; (10) Cross Teaching between CNN and Transformer; (11) FixMatch. In addition, several backbones networks (both 2D and 3D) are also supported in this repo, such as UNet, nnUNet, VNet, AttentionUNet, ENet, Swin-UNet, etc.

  • This project was originally developed for our previous works URPC (MICCAI2021 early accept). Now and future, we are still working on extending it to be more user-friendly and support more approaches to further boost and ease this topic research. If you use this codebase in your research, please cite the following works:

      @article{luo2021ctbct,
      title={Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer},
      author={Luo, Xiangde and Hu, Minhao and Song, Tao and Wang, Guotai and Zhang, Shaoting},
      booktitle={Medical Imaging with Deep Learning},
      year={2022}}
    
      @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}}
       
      @InProceedings{luo2021dtc,
      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},
      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
2022-04 X. Wang and S. Chen SSA-Net: Spatial Self-Attention Network for COVID-19 Pneumonia Infection Segmentation with Semi-supervised Few-shot Learning None MedIA2022
2022-04 Z. Zhang and X. Tian Discriminative Error Prediction Network for Semi-supervised Colon Gland Segmentation None MedIA2022
2022-04 Z. Xiao and W. Zhang Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-Aware Guided Semi-Supervised Medical Image Segmentation None SSRN
2022-04 K. Han and Z. Liu An Effective Semi-supervised Approach for Liver CT Image Segmentation None JBHI2022
2022-04 J. Yang and Q. Chen Self-Supervised Sequence Recovery for SemiSupervised Retinal Layer Segmentation None JBHI2022
2022-04 T. Cheng and C. Cheng Feature-enhanced Adversarial Semi-supervised Semantic Segmentation Network for Pulmonary Embolism Annotation None Arxiv
2022-04 K. Wang and Y. Wang Semi-supervised Medical Image Segmentation via a Tripled-uncertainty Guided Mean Teacher Model with Contrastive Learning None MedIA2022
2022-04 M. Liu and Q. He CCAT-NET: A Novel Transformer Based Semi-supervised Framework for Covid-19 Lung Lesion Segmentation None Arxiv
2022-03 Y. Liu and G. Carneiro Translation Consistent Semi-supervised Segmentation for 3D Medical Images Code Arxiv
2022-03 Z. Xu and R. Tong All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation None JBHI2022
2022-03 M. Huang and Q. Feng Semi-Supervised Hybrid Spine Network for Segmentation of Spine MR Images Code Arxiv
2022-03 S. Adiga V and H. Lombaert Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation None Arxiv
2022-03 M. Tran and T. Peng S5CL: Unifying Fully-Supervised, Self-Supervised, and Semi-Supervised Learning Through Hierarchical Contrastive Learning Code Arxiv
2022-03 M. Waerebeke and J. Dole On the pitfalls of entropy-based uncertainty for multi-class semi-supervised segmentation None Arxiv
2022-03 W. Cui and R. M. Leahy Semi-supervised Learning using Robust Loss None Arxiv
2022-03 Y. Wu and J. Cai Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation None Arxiv
2022-02 Y. Hua and L. Zhang Uncertainty-Guided Voxel-Level Supervised Contrastive Learning for Semi-Supervised Medical Image Segmentation None IJNS2022
2022-02 Y. Shu and W. Li Cross-Mix Monitoring for Medical Image Segmentation with Limited Supervision None TMM2022
2022-02 H. Huang and H. Hu MTL-ABS3Net: Atlas-Based Semi-Supervised Organ Segmentation Network with Multi-Task Learning for Medical Images None JHBI2022
2022-02 H. Wu and J. Qin Semi-supervised Segmentation of Echocardiography Videos via Noise-resilient Spatiotemporal Semantic Calibration and Fusion None MedIA2022
2022-02 Z. Liu and C. Zhao Semi-supervised Medical Image Segmentation via Geometry-aware Consistency Training None Arxiv
2022-02 X. Zhao and G. Li Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation Code ISBI2022
2022-02 H. Basak and A. Chatterjee An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation Code ISBI2022
2022-01 Q. Chen and D. Ming Semi-supervised 3D Medical Image Segmentation Based on Dual-task Consistent joint Leanrning and Task-Level Regularization None TCBB2022
2022-01 H. Yao and X. Li Enhancing Pseudo Label Quality for Semi-Supervised Domain-Generalized Medical Image Segmentation None AAAI2022
2021-12 S. Li and X. Yang Semi-supervised Cardiac MRI Segmentation Based on Generative Adversarial Network and Variational Auto-Encoder None BIBM2021
2021-12 N. Zhang and Y. Zhang Semi-supervised Medical Image Segmentation with Distribution Calibration and Non-local Semantic Constraint None BIBM2021
2021-12 S. Liu and G. Cao Shape-aware Multi-task Learning for Semi-supervised 3D Medical Image Segmentation None BIBM2021
2021-12 X. Xu and P. Yan Shadow-consistent Semi-supervised Learning for Prostate Ultrasound Segmentation Code TMI2021
2021-12 L. Hu and Y. Wang Semi-supervised NPC segmentation with uncertainty and attention guided consistency None KBS2021
2021-12 J. Peng and M. Pedersoli Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels Code NeurIPS2021
2021-12 Y. Xie and Y. Xia Intra- and Inter-pair Consistency for Semi-supervised Gland Segmentation None TIP2021
2021-12 K. Chaitanya and E. Konukoglu Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation Code Arxiv
2021-12 M. Xu and J. Jacob Learning Morphological Feature Perturbations for Semi-Supervised Segmentation Code MIDL2022
2021-12 X. Luo and S. Zhang Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer Code MIDL2022
2021-12 Y. Zhang and J. Zhang Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation None Arxiv
2021-12 J. Wang and Q. Zhou Separated Contrastive Learning for Organ-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotat Code AAAI2022
2021-12 J. Chen and Y. Lu MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification Code Arxiv
2021-12 C. Seibold and R. Stiefelhagen Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation None AAAI2022
2021-11 X. Zheng and C. Sham Uncertainty-Aware Deep Co-training for Semi-supervised Medical Image Segmentation None Arxiv
2021-11 J. Peng and M. Pedersoli Diversified Multi-prototype Representation for Semi-supervised Segmentation Code Arxiv
2021-10 J. Hou and J. Deng Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations None WACV2021
2021-10 M. Xu and J. Jacob MisMatch: Learning to Change Predictive Confidences with Attention for Consistency-Based, Semi-Supervised Medical Image Segmentation None Arxiv
2021-10 H. Wu and J. Qin Collaborative and Adversarial Learning of Focused and Dispersive Representations for Semi-supervised Polyp Segmentation None ICCV2021
2021-10 Y. Shi and Y. Gao Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation Code TMI2021
2021-09 G. Wang and S. Zhang Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention Code TMI2021
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 Q. Xu and X. Wang Semi-supervised Medical Image Segmentation with Confidence Calibration None IJCNN
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 A. Chartsias and S. A. Tsaftaris Disentangle, Align and Fuse for Multimodal and Semi-Supervised Image Segmentation Code TMI2021
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
2016-09 D. Mahapatra Semi-supervised learning and graph cuts for consensus based medical image segmentation None PR2016

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: luoxd1996@gmail.com or QQ Group (Chinese):906808850.

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

License:MIT License


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