Instructions for the removal of duplicate image files from within individual ISIC datasets and across all ISIC datasets.

ISIC 2019 - Skin Lesion Analysis Towards Melanoma Detection

Skin Lesion Analysis Towards Melanoma Detection

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

Source code and experiments for the paper: "Dark Corner on Skin Lesion Image Dataset: Does it matter?"

Analysis of the dermoscopic image processing pipeline toward optimally segmenting skin lesion regions and classifying lesion types using adversarial and generative deep learning.

ISIC2019 skin lesion classification (binary & multi-class) as well as segmentation pipelines using VGG16_BN and visual attention blocks. The project features improving the results found in the literature by implementing an ensemble architecture. This project was developed for "Computer Aided Diagnosis - CAD" course for MAIA masters program.

Developing a CNN-based model to diagnose skin cancer using the ISIC-2019 dataset.

The aim of this study is to develop a deep learning model using CNNs for accurate skin cancer diagnosis from the ISIC-2019 dataset and to optimize hyperparameters using differential evolution algorithms.