An incomplete list of self-supervised papers related to medical imaging, with a focus on analysis.
- SMORE: A Self-Supervised Anti-Aliasing and Super-Resolution Algorithm for MRI Using Deep Learning. TMI.
- Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation. TMI.
- Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning. TMI.
- Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations. TMI.
- A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning. Medical Image Analysis.
- Modality alignment contrastive learning for severity assessment of COVID-19 from lung ultrasound and clinical information. Medical Image Analysis.
- Context Matters: Graph-based Self-supervised Representation Learning for Medical Images. (Accepted by) AAAI 2021. [Code]
- MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. arXiv.
- Big Self-Supervised Models Advance Medical Image Classification. arXiv.
Representation Learning
- Self-Supervised Contrastive Video-Speech Representation Learning for Ultrasound. MICCAI 2020.
- Rubik’s Cube+: A self-supervised feature learning framework for 3D medical image analysis. Medical Image Analysis.
- Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis. TMI.
- ⭐ 3D Self-Supervised Methods for Medical Imaging. NeurIPS 2020. [Code]
- Self-Supervised Pretraining with DICOM metadata in Ultrasound Imaging. Machine Learning for Healthcare Conference 2020.
- AF-SEG: An Annotation-Free Approach for Image Segmentation by Self-Supervision and Generative Adversarial Network. ISBI 2020.
- A Multi-Task Self-Supervised Learning Framework for Scopy Images. ISBI 2020.
- Self-Supervised Representation Learning for Ultrasound Video. ISBI 2020.
- Self-Supervision vs. Transfer Learning: Robust Biomedical Image Analysis Against Adversarial Attacks. ISBI 2020.
- Self-Supervised, Semi-Supervised, Multi-Context Learning for the Combined Classification and Segmentation of Medical Images (Student Abstract). AAAI 2020.
Detection
Segmentation
- ⭐ Revisiting Rubik’s Cube: Self-supervised Learning with Volume-Wise Transformation for 3D Medical Image Segmentation. MICCAI 2020.
- Contrastive Rendering for Ultrasound Image Segmentation. MICCAI 2020.
- Region-of-Interest Guided Supervoxel Inpainting for Self-supervision. MICCAI 2020.
- Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy. MICCAI 2020.
- ⭐ Contrastive learning of global and local features for medical image segmentation with limited annotations. NeurIPS 2020. [Code]
- Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation. ECCV 2020. [Code]
- AF-SEG: An Annotation-Free Approach for Image Segmentation by Self-Supervision and Generative Adversarial Network. ISBI 2020.
- Leveraging Self-supervised Denoising for Image Segmentation. ISBI 2020.
- PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation. arXiv. [Code]
Denoising, Super Resolution
- Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning. NeurIPS 2020. [Code]
Domain Adaptation
- Dual-Task Self-supervision for Cross-modality Domain Adaptation. MICCAI 2020.
- Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking. MICCAI 2020.
Shape Analysis
- Self-supervised Discovery of Anatomical Shape Landmarks. MICCAI 2020.
Image Synthesis
- Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis. TMI. [Code]
- Auto-GAN: Self-Supervised Collaborative Learning for Medical Image Synthesis. AAAI 2020.
Representation Learning
- How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning. MICCAI 2019. [Code]
- Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik’s Cube. MICCAI 2019.
- Self-supervised learning for medical image analysis using image context restoration. Medical Image Analysis.
- Multimodal self-supervised learning for medical image analysis. NeurIPS 2019 Workshops.
- Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data. ISBI 2019.
Segmentation
- Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction. MICCAI 2019.
Others
- From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI. NeurIPS 2019.
- Deep Lesion Graph in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database. CVPR 2018.
- Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks. MICCAI 2018.
- Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.
- Self supervised deep representation learning for fine-grained body part recognition. ISBI 2017.
- Self-Supervised Learning for Spinal MRIs. 3rd Workshop on Deep Learning in Medical Image Analysis.
Resources on self-supervised learning in general.
- Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey. 2019.
- Self-supervised Learning: Generative or Contrastive. 2020.
- A Survey on Contrastive Self-supervised Learning. 2020.
- A Survey on Semi-, Self- and Unsupervised Learning in Image Classification. 2020.
- Contrastive Representation Learning: A Framework and Review. 2020.
- ⭐ Self-Supervised Representation Learning. Lil'Log. 2019.
- Contrastive Self-Supervised Learning. Ankesh Anand. 2020.
- Self-Supervised Section from LeCun's Deep Learning Course at NYU. 2020.
- ⭐ CVPR 2020 Tutorial
- LeCun - Self-Supervised Learning
- Contrastive Learning: A General Self-supervised Learning Approach. Yonglong Tian. MIT CSAIL.