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https://github.com/SaeedShurrab/awesome-self-supervised-learning-in-medical-imaging
This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field
https://github.com/SaeedShurrab/awesome-self-supervised-learning-in-medical-imaging
List: awesome-self-supervised-learning-in-medical-imaging
contrastive-learning downstream-tasks knowledge-transfer medical-image-dataset medical-image-processing medical-imaging pretext-task research-paper self-supervised-learning
Last synced: about 2 months ago
JSON representation
This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field
- Host: GitHub
- URL: https://github.com/SaeedShurrab/awesome-self-supervised-learning-in-medical-imaging
- Owner: SaeedShurrab
- Created: 2021-07-02T09:02:21.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2024-03-06T21:40:05.000Z (6 months ago)
- Last Synced: 2024-05-21T16:10:53.565Z (4 months ago)
- Topics: contrastive-learning, downstream-tasks, knowledge-transfer, medical-image-dataset, medical-image-processing, medical-imaging, pretext-task, research-paper, self-supervised-learning
- Homepage:
- Size: 1.56 MB
- Stars: 135
- Watchers: 3
- Forks: 13
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesomeai - Self-Supervised Learning in Medical Imaging
- awesome-ai-awesomeness - Self-Supervised Learning in Medical Imaging
- ultimate-awesome - awesome-self-supervised-learning-in-medical-imaging - This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field. (Other Lists / PowerShell Lists)
README
# Awesome Self-Supervised Learning in Medical Imaging [](https://awesome.re/)
This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field. Inspired by [awesome-self-supervised-learning](https://github.com/jason718/awesome-self-supervised-learning)
#### What is self-supervised learning?
Self-Supervised learning (SSL) is a hybrid learning approach that combines both supervised and unsupervised learning simultaneously. More clearly, SSL is an approach that aims at learning semantically useful features for a certain task by generating supervisory signal from a pool of unlabeled data without the need for human annotation. These representations is then used for subsequent tasks where the amount of labeled data is limited.
Self-Supervised Learning pipelines in computer vision
#### Why Self-Supervised learning in medical imaging ?
* Unlabeled medical imaging data is a abundant, but human annotated data is scarce.
* building a large enough human annotated medical imaging datasets is:
1. Expensive.
2. Time consuming.
3. Requires experienced personnel.
4. Prone to patients’ privacy preserving issues.
This repository is a continuation of our survey in the field, please read and consider citing it in your work:
```
@article{shurrab2022self,
title={Self-supervised learning methods and applications in medical imaging analysis: A survey},
author={Shurrab, Saeed and Duwairi, Rehab},
journal={PeerJ Computer Science},
volume={8},
pages={e1045},
year={2022},
publisher={PeerJ Inc.}
}
```
## Call for Contribution
Please help contribute this list by contacting [me](https://github.com/SaeedShurrab) or add [pull request](https://github.com/SaeedShurrab/awesome-selef-supervised-learning-in-medical-imaging/pulls)
Markdown format: height
```
- Paper Name.
[[pdf]](link)
[[code]](link)
- Author 1, Author 2, and Author 3. *Conference Year*
```
## Criteria
1. A list of **recent self-supervised learning papers** in medical imaging published since **2017**.
2. Papers are collected from peer-reviewed journals and high reputed conferences. However, it might have recent papers on arXiv.
3. A meta-data is required along with the paper, e.g. category.
## List of Journals / Conferences (J/C):
- **[IEEE Access](https://ieeeaccess.ieee.org/)**
- **[IEEE Transaction on Medical Imaging (IEEE-TMI)](https://ieee-tmi.org/)**
- **[IEEE Transaction on Biomedical Engineering (IEEE-TBME)](http://tbme.embs.org/)**
- **[IEEE Journal of Biomedical and Health Informatics (IEEE-JBHI)](http://jbhi.embs.org/)**
- **[IEEE Transactions on Image Processing (IEEE-TIP)](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83)**
- **[Applied Soft Computing (ASC)](https://www.sciencedirect.com/journal/applied-soft-computing)**
- **[Computer in Biology and Medicine (CBM)]()**
- **[Computerized Medical Imaging and Graphics (CMIG)](https://www.sciencedirect.com/journal/computerized-medical-imaging-and-graphics)**
- **[Medical Image Analysis (MedIA)](https://www.journals.elsevier.com/medical-image-analysis/)**
- **[Machine Learning with Applications (MLwA)](https://www.sciencedirect.com/journal/machine-learning-with-applications)**
- **[International Journal of Computer Assisted Radiology and Surgery (IJCARS)](https://link.springer.com/journal/11548)**
- **[Nature Machine Intelligence (NMI)](https://www.nature.com/natmachintell/)**
- **[Pattern Recognition](https://www.sciencedirect.com/science/journal/00313203)**
- **[Expert Systems with Applications (ESA)](https://www.sciencedirect.com/journal/expert-systems-with-applications)**
- **[Neurocomputing](https://www.sciencedirect.com/journal/neurocomputing)**
- **[Diagnostics](https://www.mdpi.com/journal/diagnostics)**
- **Computer Vision and Pattern Recognition (CVPR)**
- **Proceedings of Machine Learning Research (PMLR)**
- **International Conference on Machine Learning (ICML)**
- **IEEE International Symposium on Biomedical Imaging (ISBI)**
- **International Conference on Learning Representations (ICLR)**
- **Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)**
- **Annual Conference on Neural Information Processing Systems (NIPS)**
- **International Conference on Medical Imaging with Deep Learning (MIDL)**
- **International Workshop on Deep Learning in Medical Image Analysis (DLMIA)**
- **International Conference on Information Processing in Medical Imaging (IPMI)**
- **IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)**
- **Joint European Conference on Machine Learning and Knowledge Discovery in Databases (JECMLKDD)**
- **International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)**
----------------------------------------
## 2022
| Paper title | Journal/Conference | Category | Paper link | Code link |
| :----------------------------------------------------------: | :----------------: | :--------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
| COVID-19 Infection Segmentation and Severity Assessment Using a Self-Supervised Learning Approach | Diagnostics | Multiple-tasks/Multi-tasking | [Link](https://doi.org/10.3390/diagnostics12081805) | NA |
| Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification | MICCAI | Contrastive | [Link](http://dx.doi.org/10.1007/978-3-030-87196-3_6) | [pytorch](https://github.com/Duplums/yAwareContrastiveLearning) |
| How Transferable are Self-supervised Features in Medical Image Classification Tasks? | PMLR | Contrastive | [Link](https://proceedings.mlr.press/v158/truong21a.html) | NA |
| Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning | ICLR | Contrastive | [Link](https://openreview.net/forum?id=kQ2SOflIOVC) | [pytorch](https://github.com/TencentAILabHealthcare/Few-shot-WSI) |
| Intra- and Inter-Slice Contrastive Learning for Point Supervised OCT Fluid Segmentation | IEEE-TIP | Contrastive | [Link](https://ieeexplore.ieee.org/abstract/document/9709199) | [pytorch](https://github.com/lphxx6222712/ISCLNet) |
| Multimodal image encoding pre-training for diabetic retinopathy grading | CBM | Generative | [Link](https://www.sciencedirect.com/science/article/pii/S0010482522000944) | NA |
| Self-supervised Learning for Few-shot Medical Image Segmentation | IEEE-TMI | NA | [Link](https://ieeexplore.ieee.org/abstract/document/9709261) | [pytorch](https://github.com/cheng-01037/Self-supervised-Fewshot-Medical-Image-Segmentation) |
| Self supervised contrastive learning for digital histopathology | MLwA | Contrastive | [Link](https://doi.org/10.1016/j.mlwa.2021.100198) | [pytorch](https://github.com/ozanciga/self-supervised-histopathology) |
| DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer | MedIA | Contrastive | [Link](https://doi.org/10.1016/j.media.2022.102464) | [DLUP, VISSL, pytorch](https://github.com/NKI-AI/hissl) |
| Deep Contrastive Learning Based Tissue Clustering for Annotation-free Histopathology Image Analysis | CMIG | Contrastive | [Link](https://doi.org/10.1016/j.compmedimag.2022.102053) | NA |
| ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics | CVPR | Contrastive | [Link](https://openaccess.thecvf.com/content/CVPR2022/html/Taleb_ContIG_Self-Supervised_Multimodal_Contrastive_Learning_for_Medical_Imaging_With_Genetics_CVPR_2022_paper.html) | [pytorch](https://github.com/HealthML/ContIG) |
| Self-Supervised Learning Methods for Label-Efficient Dental Caries Classification | Diagnostics | Contrastive | [Link](https://doi.org/10.3390/diagnostics12051237) | NA |
## 2021
| Paper title | Journal/Conference | Category | Paper link | Code link |
| :----------------------------------------------------------: | :-----------------: | :--------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
| Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-Supervised Learning | IEEE-TMI | Multiple-tasks/Multi-tasking | [Link](https://doi.org/10.1109/TMI.2021.3060634) | [tensorflow](https://github.com/fhaghighi/TransVW/tree/master/keras)
[pytorch](https://github.com/fhaghighi/TransVW/tree/master/pytorch) |
| Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling | ICML | Multiple-tasks/Multi-tasking | [Link](https://arxiv.org/pdf/2104.04323.pdf) | [tensorflow](https://github.com/bayer-science-for-a-better-life/contrastive-reconstruction) |
| How Transferable are Self-supervised Features in Medical Image Classification Tasks? | PMLR | Contrastive | [Link](https://proceedings.mlr.press/v158/truong21a.html) | NA |
| Multimodal Self-supervised Learning for Medical Image Analysis | IPMI | Predictive | [Link](https://link.springer.com/chapter/10.1007/978-3-030-78191-0_51) | NA |
| Self-supervised multimodal reconstruction pre-training for retinal computer-aided diagnosis | ESA | Generative | [Link](https://www.sciencedirect.com/science/article/pii/S0957417421009982) | NA |
| MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation | ArXiv | Contrastive | [Link](https://arxiv.org/abs/2102.10663) | NA |
| COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction | ArXiv | Contrastive | [Link](https://arxiv.org/abs/2101.04909) | [pytorch](https://github.com/facebookresearch/CovidPrognosis) |
| Momentum contrastive learning for few-shot COVID-19 diagnosis from chest CT images | Pattern Recognition | Contrastive | [Link](https://www.sciencedirect.com/science/article/abs/pii/S0031320321000133) | NA |
| Big Self-Supervised Models Advance Medical Image Classification | ArXiv | Contrastive | [Link](https://arxiv.org/abs/2101.05224) | NA |
| Self-supervised Multi-task Representation Learning for Sequential Medical Images | JECMLKDD | Multiple-tasks/Multi-tasking | [Link](https://link.springer.com/chapter/10.1007/978-3-030-86523-8_47) | NA |
| Self-path: Self-supervision for classification of pathology images with limited annotations | IEEE-TMI | Multiple-tasks/Multi-tasking | [Link](https://ieeexplore.ieee.org/document/9343323) | NA |
| Twin self-supervision based semi-supervised learning (TS-SSL): Retinal anomaly classification in SD-OCT images | Neurocomputing | Multiple-tasks/Multi-tasking | [Link](https://www.sciencedirect.com/science/article/abs/pii/S0925231221012352) | [tensorflow](https://github.com/ZhangYH0502/TS-SSL.) |
| Rotation-oriented collaborative self-supervised learning for retinal disease diagnosis. | IEEE-TMI | Multiple-tasks/Multi-tasking | [Link](https://ieeexplore.ieee.org/document/9411868) | [tensorflow](https://github.com/xmengli999/Rotation-oriented-self-supervised) |
| Volumetric white matter tract segmentation with nested self-supervised learning using sequential pretext tasks | MedIA | Multiple-tasks/Multi-tasking | [Link](https://www.sciencedirect.com/science/article/abs/pii/S1361841521001407) | NA |
## 2020
| Paper title | Journal/Conference | Category | Paper link | Code link |
| :----------------------------------------------------------: | :----------------: | :--------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
| Auto-GAN: Self-Supervised Collaborative Learning for Medical Image Synthesis | AAAI | Generative | [Link](https://doi.org/10.1609/aaai.v34i07.6619) | NA |
| Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-supervised Medical Image Segmentation | MICCAI | Predictive | [Link](https://link.springer.com/chapter/10.1007/978-3-030-59710-8_60) | NA |
| Rubik’s Cube+: A self-supervised feature learning framework for 3D medical image analysis | MedIA | Predictive | [Link](https://www.sciencedirect.com/science/article/abs/pii/S1361841520301109) | NA |
| Self-Supervised Learning Based on Spatial Awareness for Medical Image Analysis | IEEE Access | Predictive | [Link](https://ieeexplore.ieee.org/document/9186121) | NA |
| Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy | MICCAI | Generative | [Link](https://link.springer.com/chapter/10.1007/978-3-030-59713-9_38) | [pytorch](https://gitlab.com/matzkin/headctools) |
| Learning the retinal anatomy from scarce annotated data using self-supervised multimodal reconstruction | ASC | Generative | [Link](https://www.sciencedirect.com/science/article/pii/S1568494620301502) | NA |
| Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation | ArXiv | Generative | [Link](https://arxiv.org/abs/2012.10160) | NA |
| Multi-modal self-supervised pre-training for joint optic disc and cup segmentation in eye fundus images | ICASSP | Generative | [Link](https://ieeexplore.ieee.org/abstract/document/9053551) | NA |
| Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy | NMI | Generative | [Link](https://www.nature.com/articles/s42256-020-00247-1) | [tensorflow](https://github.com/theislab/DeepRT) |
| Leveraging Self-supervised Denoising for Image Segmentation | ISBI | Generative | [Link](https://ieeexplore.ieee.org/abstract/document/9098559) | [tensorflow](https://github.com/juglab/VoidSeg) |
| Self-Supervised Pretraining with DICOM metadata in Ultrasound Imaging | PMLR | Generative | [Link](https://proceedings.mlr.press/v126/hu20a.html) | NA |
| Revisiting rubik’s cube: Self-supervised learning with volume-wise transformation for 3d medical image segmentation | MICCAI | Generative | [Link](https://link.springer.com/chapter/10.1007/978-3-030-59719-1_24) | NA |
| Semi-supervised breast cancer histology classification using deep multiple instance learning and contrast predictive coding | ArXiv | Contrastive | [Link](https://arxiv.org/abs/1910.10825) | NA |
| Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning | ArXiv | Contrastive | [Link](https://arxiv.org/abs/2006.05798) | NA |
| PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation | ArXiv | Contrastive | [Link](https://arxiv.org/abs/2011.12640) | [pytorch](https://github.com/YtongXie/PGL) |
| Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis | IEEE-TMI | Contrastive | [Link](https://ieeexplore.ieee.org/document/9139411) | [pytorch](https://github.com/xmengli999/self_supervised) |
| MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models | PMLR | Contrastive | [Link](https://proceedings.mlr.press/v143/sowrirajan21a.html) | [pytorch](https://github.com/stanfordmlgroup/MoCo-CXR) |
| Contrastive learning of global and local features for medical image segmentation with limited annotations | ArXiv | Contrastive | [Link](https://arxiv.org/abs/2006.10511) | [tensorflow](https://github.com/krishnabits001/domain_specific_cl) |
| Self-Supervised Representation Learning for Ultrasound Video | ISBI | Multiple-tasks/Multi-tasking | [Link](https://ieeexplore.ieee.org/abstract/document/9098666) | NA |
| A Multi-Task Self-Supervised Learning Framework for Scopy Images | ISBI | Multiple-tasks/Multi-tasking | [Link](https://ieeexplore.ieee.org/abstract/document/9098527) | NA |
| 3D Self-Supervised Methods for Medical Imaging--update references | NIPS | Multiple-tasks/Multi-tasking | [Link](https://proceedings.neurips.cc/paper/2020/file/d2dc6368837861b42020ee72b0896182-Paper.pdf) | [tensorflow](https://github.com/HealthML/self-supervised-3d-tasks) |
| Retinal Image Classification by Self-Supervised Fuzzy Clustering Network | IEEE Access | Multiple-tasks/Multi-tasking | [Link](https://ieeexplore.ieee.org/document/9091815) | NA |
| Learning semantics-enriched representation via self-discovery, self-classification, and self-restoration | MICCAI | Multiple-tasks/Multi-tasking | [Link](https://link.springer.com/chapter/10.1007/978-3-030-59710-8_14) | [pytorch](https://github.com/fhaghighi/SemanticGenesis) |
| SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation | ArXiv | Multiple-tasks/Multi-tasking | [Link](https://arxiv.org/abs/2010.06107) | NA |
## 2019
| Paper title | Journal/Conference | Category | Paper link | Code link |
| :----------------------------------------------------------: | :----------------: | :--------------------------: | :----------------------------------------------------------: | :-------------------------------------------------------: |
| Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction | MICCAI | Predictive | [Link](https://link.springer.com/chapter/10.1007/978-3-030-32245-8_60) | NA |
| Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik’s Cube | MICCAI | Predictive | [Link](https://link.springer.com/chapter/10.1007/978-3-030-32251-9_46) | NA |
| Self-supervised learning for medical image analysis using image context restoration | MedIA | Generative | [Link](https://www.sciencedirect.com/science/article/abs/pii/S1361841518304699) | NA |
| Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis | MICCAI | Generative | [Link](https://link.springer.com/chapter/10.1007/978-3-030-32251-9_42) | [tensorflow](https://github.com/MrGiovanni/ModelsGenesis) |
| Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data | ISBI | Multiple-tasks/Multi-tasking | [Link](https://ieeexplore.ieee.org/document/8759553/) | NA |
## 2018
| Paper title | Journal/Conference | Category | Paper link | Code link |
| :----------------------------------------------------------: | :----------------: | :--------: | :----------------------------------------------------------: | :-------: |
| Exploiting the potential of unlabeled endoscopic video data with self-supervised learning | IJCARS | Generative | [Link](https://link.springer.com/article/10.1007/s11548-018-1772-0) | NA |
| Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks | MICCAI | Predictive | [Link](https://link.springer.com/chapter/10.1007/978-3-030-00931-1_76) | NA |
## 2017
| Paper title | Journal/Conference | Category | Paper link | Code link |
| :----------------------------------------------------------: | :----------------: | :---------: | :----------------------------------------------------------: | :-------: |
| Self-supervised Learning for Spinal MRIs | DLMIA | Contrastive | [Link](https://link.springer.com/chapter/10.1007/978-3-319-67558-9_34) | NA |
| Self supervised deep representation learning for fine-grained body part recognition | ISBI | Predictive | [Link](https://ieeexplore.ieee.org/document/7950587) | NA |