IDRiD

This challenge evaluates automated techniques for analysis of fundus photographs. We target segmentation of retinal lesions like exudates, microaneurysms, and hemorrhages and detection of the optic disc and fovea. Also, we seek grading of fundus images according to the severity level of DR and DME.

DRIVE

Develop a system to automatically segment vessels in human retina fundus images.

ODIR-2019

北京大学国际眼底图像智能识别竞赛 Peking University International Competition on Ocular Disease Intelligent Recognition

COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020

This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.

FeTA - Fetal Tissue Annotation Challenge

Fetal Tissue Annotation Challenge

STOIC2021 - COVID-19 AI Challenge

COVID-19 Artificial Intelligence Challenge: automated diagnosis, and prognostic evaluation based on computed tomography

The PI-CAI Challenge

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

BCNB

Early Breast Cancer Core-Needle Biopsy WSI Dataset

SynthRAD2023

SynthRAD is the first challenge on automatic generation of synthetic computed tomography (sCT) for radiotherapy

Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022

Universal Lesion Segmentation Challenge '23