Stars
A data management platform for the web, developed by Kitware
EASY (dermoscopy expert annotation) agreement study data
Loading and handling microscopy data in blender
Official implementation of DoubleU-Net for Semantic Image Segmentation in TensorFlow & Pytorch (Nominated for Best Paper Award (IEEE CBMS))
Scripts for 3d reconstruction from histological slices
Scripts written and applications developed in preparing the contextual dermoscopic image database for the SIIM-ISIC Melanoma Classification competition. The competition was hosted on Kaggle during …
SIIM/ISIC 2020 Challenge Winning Algorithm (All Data Are Ext)
The SCIN dataset contains 10,000+ images of dermatology conditions, crowdsourced with informed consent from US internet users. Contributions include self-reported demographic and symptom informatio…
Exploratory data analysis of the Hospital Italiano de Buenos Aires Skin Lesions dataset shared through the ISIC Archive. The dataset is available at https://doi.org/10.34970/432362
Research model for classification and feature extraction of dermatoscopic images
Colour palettes based on blank VHS cassette packaging design
Label Studio is a multi-type data labeling and annotation tool with standardized output format
This code proposes a novel deep learning-based, fully automated approach to skin lesion segmentation, including sophisticated pre and postprocessing approaches. We use three deep learning models, i…
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Official implementation of ResUNet++, CRF, and TTA for segmentation of medical images (IEEE JBIHI)
Official code for ResUNetplusplus for medical image segmentation (TensorFlow & Pytorch implementation)
The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.
📖 An opinionated intermediate/advanced Git book
🏡 A Book for Anyone to Get Started with Unix
4102A curated list of awesome R packages, frameworks and software.