VESSEL12

The VESSEL12 challenge compares methods for automatic (and semi-automatic) segmentation of blood vessels in the lungs from CT images.

PROMISE12

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

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.

orCaScore

The purpose of the orCaScore challenge is to compare methods for automatic and semi-automatic coronary artery calcium scoring in cardiac CT scans. This evaluation framework was launched at the MICCAI 2014 workshops in Boston, USA, where we organized the Challenge on Automatic Coronary Calcium Scoring.

Parse2022

It is of significant clinical interest to study pulmonary artery structures in the field of medical image analysis. One prerequisite step is to segment pulmonary artery structures from CT with high accuracy and low time-consuming. The segmentation of pulmonary artery structures benefits the quantification of its morphological changes for diagnosis of pulmonary hypertension and thoracic surgery. However, due to the complexity of pulmonary artery topology, automated segmentation of pulmonary artery topology is a challenging task. Besides, the open accessible large-scale CT data with well labeled pulmonary artery are scarce (The large variations of the topological structures from different patients make the annotation an extremely challenging process). The lack of well labeled pulmonary artery hinders the development of automatic pulmonary artery segmentation algorithm. Hence, we try to host the first Pulmonary ARtery SEgmentation challenge in MICCAI 2022 (Named Parse2022) to start a new research topic.

RAVIR

A dataset for semantic segmentation and quantitative analysis of retinal arteries and veins in infrared reflectance imaging

MICCAI HECKTOR 2022

Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images

Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022