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This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field

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Awesome Self-Supervised Learning in Medical Imaging Awesome

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

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 or add pull request

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):


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 NA
Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification MICCAI Contrastive Link pytorch
How Transferable are Self-supervised Features in Medical Image Classification Tasks? PMLR Contrastive Link NA
Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning ICLR Contrastive Link pytorch
Intra- and Inter-Slice Contrastive Learning for Point Supervised OCT Fluid Segmentation IEEE-TIP Contrastive Link pytorch
Multimodal image encoding pre-training for diabetic retinopathy grading CBM Generative Link NA
Self-supervised Learning for Few-shot Medical Image Segmentation IEEE-TMI NA Link pytorch
Self supervised contrastive learning for digital histopathology MLwA Contrastive Link pytorch
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 DLUP, VISSL, pytorch
Deep Contrastive Learning Based Tissue Clustering for Annotation-free Histopathology Image Analysis CMIG Contrastive Link NA
ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics CVPR Contrastive Link pytorch
Self-Supervised Learning Methods for Label-Efficient Dental Caries Classification Diagnostics Contrastive Link 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 tensorflow
pytorch
Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling ICML Multiple-tasks/Multi-tasking Link tensorflow
How Transferable are Self-supervised Features in Medical Image Classification Tasks? PMLR Contrastive Link NA
Multimodal Self-supervised Learning for Medical Image Analysis IPMI Predictive Link NA
Self-supervised multimodal reconstruction pre-training for retinal computer-aided diagnosis ESA Generative Link NA
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation ArXiv Contrastive Link NA
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction ArXiv Contrastive Link pytorch
Momentum contrastive learning for few-shot COVID-19 diagnosis from chest CT images Pattern Recognition Contrastive Link NA
Big Self-Supervised Models Advance Medical Image Classification ArXiv Contrastive Link NA
Self-supervised Multi-task Representation Learning for Sequential Medical Images JECMLKDD Multiple-tasks/Multi-tasking Link NA
Self-path: Self-supervision for classification of pathology images with limited annotations IEEE-TMI Multiple-tasks/Multi-tasking Link NA
Twin self-supervision based semi-supervised learning (TS-SSL): Retinal anomaly classification in SD-OCT images Neurocomputing Multiple-tasks/Multi-tasking Link tensorflow
Rotation-oriented collaborative self-supervised learning for retinal disease diagnosis. IEEE-TMI Multiple-tasks/Multi-tasking Link tensorflow
Volumetric white matter tract segmentation with nested self-supervised learning using sequential pretext tasks MedIA Multiple-tasks/Multi-tasking Link NA

2020

Paper title Journal/Conference Category Paper link Code link
Auto-GAN: Self-Supervised Collaborative Learning for Medical Image Synthesis AAAI Generative Link NA
Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-supervised Medical Image Segmentation MICCAI Predictive Link NA
Rubik’s Cube+: A self-supervised feature learning framework for 3D medical image analysis MedIA Predictive Link NA
Self-Supervised Learning Based on Spatial Awareness for Medical Image Analysis IEEE Access Predictive Link NA
Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy MICCAI Generative Link pytorch
Learning the retinal anatomy from scarce annotated data using self-supervised multimodal reconstruction ASC Generative Link NA
Multimodal Transfer Learning-based Approaches for Retinal Vascular Segmentation ArXiv Generative Link NA
Multi-modal self-supervised pre-training for joint optic disc and cup segmentation in eye fundus images ICASSP Generative Link NA
Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy NMI Generative Link tensorflow
Leveraging Self-supervised Denoising for Image Segmentation ISBI Generative Link tensorflow
Self-Supervised Pretraining with DICOM metadata in Ultrasound Imaging PMLR Generative Link NA
Revisiting rubik’s cube: Self-supervised learning with volume-wise transformation for 3d medical image segmentation MICCAI Generative Link NA
Semi-supervised breast cancer histology classification using deep multiple instance learning and contrast predictive coding ArXiv Contrastive Link NA
Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning ArXiv Contrastive Link NA
PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation ArXiv Contrastive Link pytorch
Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis IEEE-TMI Contrastive Link pytorch
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models PMLR Contrastive Link pytorch
Contrastive learning of global and local features for medical image segmentation with limited annotations ArXiv Contrastive Link tensorflow
Self-Supervised Representation Learning for Ultrasound Video ISBI Multiple-tasks/Multi-tasking Link NA
A Multi-Task Self-Supervised Learning Framework for Scopy Images ISBI Multiple-tasks/Multi-tasking Link NA
3D Self-Supervised Methods for Medical Imaging--update references NIPS Multiple-tasks/Multi-tasking Link tensorflow
Retinal Image Classification by Self-Supervised Fuzzy Clustering Network IEEE Access Multiple-tasks/Multi-tasking Link NA
Learning semantics-enriched representation via self-discovery, self-classification, and self-restoration MICCAI Multiple-tasks/Multi-tasking Link pytorch
SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation ArXiv Multiple-tasks/Multi-tasking Link 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 NA
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik’s Cube MICCAI Predictive Link NA
Self-supervised learning for medical image analysis using image context restoration MedIA Generative Link NA
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis MICCAI Generative Link tensorflow & pytorch
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data ISBI Multiple-tasks/Multi-tasking Link 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 NA
Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks MICCAI Predictive Link NA

2017

Paper title Journal/Conference Category Paper link Code link
Self-supervised Learning for Spinal MRIs DLMIA Contrastive Link NA
Self supervised deep representation learning for fine-grained body part recognition ISBI Predictive Link NA

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