The PANORAMA Challenge - Reading Interface and Workflow Demo

PANORAMA is an all-new grand challenge with +2000 of carefully curated abdominal CECT exams, and tools to upload, run and validate AI in a secure environment, using standardized consensus-based guidelines.

RibFrac

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

AutoImplant 2021

Second MICCAI Challenge on Automatic Cranial Implant Design (AutoImplant 2021)

3D Teeth Scan Segmentation and Labeling Challenge MICCAI2022

Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and therefore ease the prediction of treatment outcomes. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.

Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022

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.

DENTEX - MICCAI23

Dental Enumeration and Diagnosis on Panoramic X- rays Challenge

CL-Detection 2023

Cephalometric landmark detection in lateral x-ray images

Vertebra segmentation and labeling

Segmentation and labeling of the vertebrae in CT scans with arbitrary field of view.

JawFracNet

Segment mandible and mandibular fractures in head CBCT scan