PROMISE12

The goal of this challenge is to compare interactive and (semi)-automatic segmentation algorithms for MRI of the prostate.

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.

CHAOS

In this challenge, you segment the liver in CT data, and segment liver, spleen, and kidneys in MRI data.

Decathlon

The Medical Segmentation Decathlon challenge tests the generalisability of machine learning algorithms when applied to 10 different semantic segmentation task.

EndoCV2020

Endoscopy computer vision challenge (EndoCV2020) introduces two core sub-themes in endoscopy: 1) artefact detection and segmentation (EAD2020) and 2) disease detection and segmentation (EDD2020).

VerSe'20

Vertebrae labelling and segmentation on a multi-centre, multi-scanner, and anatomically-diverse CT dataset.

Thyroid Nodule Segmentation and Classification

The main topic of this TN-SCUI2020 challenge is finding automatic algorithms to accurately classify the thyroid nodules in ultrasound images. It will provide the biggest public dataset of thyroid nodule with over 4500 patient cases from different ages, genders, and were collected using different ultrasound machines. Each ultrasound image is provided with its ground truth class (benign or maglinant) and a detailed delineation of the nodule. This challenge will provide a unique opportunity for participants from different backgrounds (e.g. academia, industry, and government, etc.) to compare their algorithms in an impartial way.

EndoCV2021

Endoscopy Computer Vision Challenge 2021

Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022

Foundation Model Prompting for Medical Image Classification

The primary objective of this challenge is to promote the development and evaluation of model adaptation techniques for medical image classification to leverage the existing foundation models.

Cross-Organ and Cross-Scanner Adenocarcinoma Segmentation