CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions

ISIC 2018 - Skin Lesion Classification for Melanoma Detection

Code for the paper "Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis", CVPRW 2023.

Official implementation of Deeply Supervised Skin Lesions Diagnosis with Stage and Branch Attention

StyleGAN2-ADA for generation of synthetic skin lesions

The official implementation of "TFormer: A throughout fusion transformer for multi-modal skin lesion diagnosis"

The souce code of MICCAI'23 paper: Combat Long-tails in Medical Classification with Relation-aware Consistency and Virtual Features Compensation

Skin lesion classification, using Keras and the ISIC 2020 dataset

Mutlimodality for skin lesions classification

Skin lesion image analysis that draws on meta-learning to improve performance in the low data and imbalanced data regimes.

CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions. Mirror of https://github.com/arezou-pakzad/CIRCLe

Bi-modal cnn-transformer feature extractor with prototype decision tree classifier for accurate and explainable skin lesion diagnosis.

A new approach to skin lesion classification with EnTransfer CNN: https://ieeexplore.ieee.org/document/9599051/

This repository contains code and dataset for a multiclass image classification model to detect monkeypox using the ResNet50 architecture. The project focuses on classifying skin lesion images into different categories related to monkeypox, achieving 100% accuracy.