Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Data

MetaGraspNet: a large-scale benchmark dataset for vision-driven robotic grasping via physics-based metaverse synthesis -100,000 images across 5 difficulty levels

Lesion and prostate masks for the PROSTATEx training dataset, after a lesion-by-lesion quality check.

Easiest way to run ChRIS locally.

We built a large lung CT scan dataset for COVID-19 by curating data from 7 different public datasets. These datasets have been publicly used in COVID-19 diagnosis literature and proven their effici…

Open benchmark dataset of COVID-19 related ultrasound imaging data, curated and systematically validated — Ensemble de données de référence ouvert d'imagerie échographique liées à la COVID-19, orga…

Lucid library adapted for PyTorch

COVID-Net Open Source Initiative

Segmentation and Classification models for COVID CT scans (COVID, pneumonia, normal) based on Mask R-CNN.

PST or Phase Stretch Transform is an operator that finds features in an image. PST implemented using MATLAB here, takes an intensity image I as its input, and returns a binary image out of the same…