Popular GitHub Repositories for Skin Cancer

Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

BCDU-Net : Medical Image Segmentation

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

Highly Accurate and Efficient Burn detection and Classification trained with Deep Learning Model

[arXiv] The official code for "UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation".

[WACV 2024] Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation

BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

Training and evaluating a variational autoencoder for pan-cancer gene expression data

A Machine Learning and Deep Learning based webapp used to predict multiple diseases.

HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation (WACV 2023)

[Nature Machine Intelligence 2024] Code and evaluation repository for the paper

BioDynaMo is a high-performance and modular, agent-based simulation platform.

A Python-based computer vision and AI system for skin disease recognition and diagnosis. Led end-to-end project pipeline, including data gathering, preprocessing, and training models. Utilized Keras, TensorFlow, OpenCV, and other libraries for image processing and CNN models, showcasing expertise in deep learning and machine learning techniques.

Corresponding code of 'Quiros A.C., Murray-Smith R., Yuan K. Pathology GAN: Learning deep representations of cancer tissue. Proceedings of The 3rd International Conference on Medical Imaging with Deep Learning (MIDL) 2020'

Contextual Attention Network: Transformer Meets U-Net

(BIBM22) This is the official code repository for "MALUNet: A Muti-Attention and Light-weight UNet for Skin Lesion Segmentation".

Federated Learning based Deep Learning. Docs: https://fets-ai.github.io/Front-End/

Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.