Source code for the paper 'Data Augmentation for Skin Lesion Analysis' — 🏆 Best Paper Award at the ISIC Skin Image Analysis Workshop @ MICCAI 2018

Implementation for MICCAI DART paper: 'Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification'

Experiments of the DAI in Healthcare project - skin lesions images use case - using Flower

Implementation for ICML 2022 paper: 'Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification'

This is a final-year project backend primarily focused on image classification for melanoma skin cancer. I have implemented a Convolutional Neural Network (CNN) AI model for this purpose.

Official code for our paper - "Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data".

This repository deals with generating 'malign' synthetic samples from 'benign' samples using CycleGAN to mitigate class imbalance and detecting Melanoma using a new balanced skin lesion image dataset.

Classification of malignt or benignt melanoma using the ISIC 2020 Challenge Dataset.

Multiclass Skin lesion localization and Detection with YOLOv7-XAI Framework with explainable AI

Deep learning pipeline for multi-type ISIC 2018 skin lesion classification with CNNs, preprocessing, augmentation, and training and inference support 🐙.

A collection of publicly available skin lesion datasets

Ai powered web app that can analyze a picture of a skin lesion and instantly classify it into one of 7 types - including cancerous lesions like melanoma.

This repository contains experiments using different XAI methods and ISIC2020 dataset.

Melanoma classification using computer vision techniques on SIM-ISIC 2020 dataset

A deep learning pipeline for skin lesion classification using ISIC dataset with multiple deep learning cnn algorithms and advanced preprocessing including multithreaded loading, augmentation, and performance evaluation.

Melanoma Detection Tool : Website

Melanoma Detection | Image Classification | Convolutional Neural Network

Segmentation and classification of skin lesion images from ISIC 2019 challenge dataset.

Melanoma Skin Cancer Diagnosis based on Dermoscopic Features and DNA Mutations

The project consist in a binary classification for melanoma detection. Reference was made to the Challenge proposed the International Skin Imaging Collaboration in 2016, and in particular Task 3 (Lesion Classification), using its datasets and testing the model through the same metrics.