DRIVE

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

RibFrac

Rib Fracture Detection and Classification Challenge: A large-scale benchmark of 660 CT scans with ~5,000 rib fractures (around 80Gb)

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.

ToothFairy: Cone-Beam Computed Tomography Segmentation Challenge

This is the first edition of the ToothFairy challenge organized by the University of Modena and Reggio Emilia with the collaboration of Raudboud University. This challenge aims at pushing the development of deep learning frameworks to segment the Inferior Alveolar Canal (IAC) by incrementally extending the amount of publicly available 3D-annotated Cone Beam Computed Tomography (CBCT) scans. CBCT modality is becoming increasingly important for treatment planning and diagnosis in implant dentistry and maxillofacial surgery. The three-dimensional information acquired with CBCT can be crucial to plan a vast number of surgical interventions with the aim of preserving noble anatomical structures such as the Inferior Alveolar Canal (IAC), which contains the homonymous nerve (Inferior Alveolar Nerve, IAN). Deep learning models can support medical personnel in surgical planning procedures by providing a voxel-level segmentation of the IAN automatically extracted from CBCT scans.

Surgical Planning in Pediatric Neuroblastoma

Topology-Aware Anatomical Segmentation of the Circle of Willis

Segment the Circle of Willis (CoW) vessel components for both CTA and MRA

PANORAMA

Artificial Intelligence and Radiologists at Pancreatic Cancer Diagnosis in CT

Universal Lesion Segmentation Challenge '23

AutoPET III

ToothFairy2: Multi-Structure Segmentation in CBCT Volumes

This is the second edition of the ToothFairy challenge organized by the University of Modena and Reggio Emilia with the collaboration of Radboud University Medical Center. The challenge is hosted by grand-challenge and is part of MICCAI2024.

Multi-Class Segmentation of Aortic Branches and Zones in CTA

3D Segmentation of Aortic Branches and Zones on Computed Tomography Angiography (CTA)

TopCoW 2024 Challenge

Segment, classify, and detect the Circle of Willis (CoW) for both CTA and MRA

TrackRad: Real-time tumor tracking for MRI-guided radiotherapy

Deep-learning Evaluation for Enhanced Prognostics - PSMA PET

autoPET/CT IV

Automated Lesion Segmentation in PET/CT - The human frontier

ToothFairy3: Multi-Class Segmentation in CBCT Volumes

ToothFairy3, part of the ODIN2025 challenge cluster at MICCAI2025, advances CBCT segmentation with an expanded 77-class dataset and a new emphasis on computational efficiency. It introduces two tasks: a runtime-aware multi-structure segmentation and a novel interactive track for Inferior Alveolar Canal (IAC) segmentation using minimal user input. The challenge supports the development of both automated and prompt-based interactive AI tools to enhance clinical workflows in dentistry and maxillofacial surgery.