awesome-self-supervised-learning-in-medical-imaging
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
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List of Journals / Conferences (J/C):202220212020201920182017
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2020
- 3D Self-Supervised Methods for Medical Imaging--update references
NIPS
- A Multi-Task Self-Supervised Learning Framework for Scopy Images
ISBI
- Auto-GAN: Self-Supervised Collaborative Learning for Medical Image Synthesis
AAAI
- Contrastive learning of global and local features for medical image segmentation with limited annotations
ArXiv
- Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning
ArXiv
- Learning semantics-enriched representation via self-discovery, self-classification, and self-restoration
MICCAI
List of Journals / Conferences (J/C):
2021
- Big Self-Supervised Models Advance Medical Image Classification
ArXiv
- COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction
ArXiv
- How Transferable are Self-supervised Features in Medical Image Classification Tasks?
PMLR
- MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation
ArXiv
- Momentum contrastive learning for few-shot COVID-19 diagnosis from chest CT images
Pattern Recognition
- Multimodal Self-supervised Learning for Medical Image Analysis
IPMI
2022
- ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics
CVPR
- Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification
MICCAI
- COVID-19 Infection Segmentation and Severity Assessment Using a Self-Supervised Learning Approach
Diagnostics
- Deep Contrastive Learning Based Tissue Clustering for Annotation-free Histopathology Image Analysis
CMIG
- DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer
MedIA
- Intra- and Inter-Slice Contrastive Learning for Point Supervised OCT Fluid Segmentation
IEEE-TIP
2018
2019
- Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
MICCAI
- Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik’s Cube
MICCAI
- Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
MICCAI
- Self-supervised learning for medical image analysis using image context restoration
MedIA
- Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data
ISBI
Showing a sample of 73 resources. View the full list on GitHub →