LUNA16

The LUNA16 challenge: automatic nodule detection on chest CT

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.

REFUGE

The goal of the Retinal Fundus Glaucoma Challenge (REFUGE) is to evaluate and compare automated algorithms for glaucoma detection and optic disc/cup segmentation on a common dataset of retinal fundus images.

PALM

The Pathologic Myopia Challenge (PALM) focuses on the investigation and development of algorithms associated with the diagnosis of Pathological Myopia (PM) and segmentation of lesions in fundus photos from PM patients.

PAIP 2019

PAIP2019: Liver Cancer Segmentation Task 1: Liver Cancer Segmentation Task 2: Viable Tumor Burden Estimation

iChallenge-AMD

Age-related Macular Degeneration Challenge

Cross-Modality Domain Adaptation Image Segmentation - 2021

The CrossMoDA challenge 2021 introduces the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

ATLAS R2.0 - Stroke Lesion Segmentation

Anatomical Tracings of Lesions After Stroke

autoPET

Automatic lesion segmentation in whole-body FDG-PET/CT

Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022

Cross-Modality Domain Adaptation: Segmentation & Classification

The CrossMoDA 2022 challenge is the second edition of the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

autoPET-II

Automated Lesion Segmentation in PET/CT - Domain Generalization

Universal Lesion Segmentation Challenge '23

AutoPET III

Ischemic Stroke Lesion Segmentation Challenge 2024

Pelvic Bone Fragments with Injuries Segmentation Challenge

Pelvic fracture segmentation in CT and X-ray