arezou-pakzad / CIRCLe
CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions
☆16Updated last year
Alternatives and similar repositories for CIRCLe:
Users that are interested in CIRCLe are comparing it to the libraries listed below
- Official code for Robust T-Loss for Medical Image Segmentation (MICCAI 2023)☆48Updated last year
- A collection of self-supervised papers in medical imaging.☆39Updated 3 years ago
- [Nature Medicine] The Limits of Fair Medical Imaging AI In Real-World Generalization☆26Updated last month
- Code for the paper "Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed", TMLR 2022, Bernhardt et…☆20Updated 2 years ago
- Official PyTorch Implementation for DiRA: Discriminative, Restorative, and Adversarial Learning for Self-supervised Medical Image Analysi…☆101Updated 10 months ago
- Official PyTorch Implementation and Pre-trained Models for Benchmarking Transfer Learning for Medical Image Analysis☆50Updated last year
- ☆38Updated 10 months ago
- Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation☆35Updated 3 years ago
- Code for the paper https://arxiv.org/abs/2003.00827☆99Updated 3 years ago
- [ECCV ISIC Workshop 2022 (best paper)] FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning (an official implemen…☆14Updated last year
- [IEEE Transactions on Medical Imaging 2024] Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Ide…☆19Updated last month
- Dermatology dataset composed of a diagnosis and seven-point checklist criteria labels☆77Updated 11 months ago
- Anatomy-aware self-supervised learning☆11Updated 8 months ago
- Official PyTorch repository for ...☆27Updated last year
- A collection of open-source algorithms for chest X-ray analysis☆13Updated last year
- Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation☆36Updated 3 years ago
- Anatomically-aware Uncertainty for Semi-supervised Image Segmentation