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

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

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

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.

COVID-19 Classification from 3D CT Images

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

Solution for NeurIPS 2023 - MedFM Challenge

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.

Official Code for "StAlK: Structural Alignment based Self Knowledge distillation for Medical Image Classification" Published at Knowledge Based Systems Journal

Prediction of the status of a genetic biomarker for brain cancer treatment.