A collection of resources on applications of Transformers in Medical Imaging.

Official Repository of NeurIPS 2023 - MedFM Challenge

MedViT: A Robust Vision Transformer for Generalized Medical Image Classification (Computers in Biology and Medicine 2023)

A collection of papers published in MICCAI 2024 with their code.

MedViTV2: Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood Attention

a framework for Automated Classification of Medical Images

Deep Multimodal Guidance for Medical Image Classification: https://arxiv.org/pdf/2203.05683.pdf

This repo is the official implementation of TMI2024 paper "Prompt-driven Latent Domain Generalization for Medical Image Classification".

Code for the paper "Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed", TMLR 2022, Bernhardt et al.

A reproducible 3D convolutional neural network with dual attention module (3D-DAM) for Alzheimer's disease classification

Simple study on ViT performance in medical image classification

Official repository of the paper "Explainable Deep Learning Methods in Medical Image Classification: A Survey", ACM Computing Surveys (CSUR), 2023.

Implementation of Deep Neural Networks to solve Medical Image Classification using Chest XRay Images

Code for [CVPR 2025] Domain Adaptive Diabetic Retinopathy Grading with Model Absence and Flowing Data.

Official Code for "Confidence Matters: Enhancing Medical Image Classification Through Uncertainty-Driven Contrastive Self-distillation" accepted at MICCAI2024

COVID-19 Classification from 3D CT Images

Solution for NeurIPS 2023 - MedFM Challenge

MIAFEx is a Transformer-based extractor for medical images that refines the [CLS] token to produce robust features, improving results on small or imbalanced datasets and supporting feature selection and classifier design. These features can be directly used with classical classifiers (SVM, RF, etc.) or combined with more sophisticaded approaches.

HAM10000 Skin Lesion Classification

The repository focuses on conducting Federated Learning experiments using the Intel OpenFL framework with diverse machine learning models, utilizing image and tabular datasets, applicable different domains like medicine, banking etc.