ODIR-2019

北京大学国际眼底图像智能识别竞赛 Peking University International Competition on Ocular Disease Intelligent Recognition

EndoCV2021

Endoscopy Computer Vision Challenge 2021

EndoCV2022

Developing methods for "detection task'' and ''segmentation task'' for endoscopic video sequence data

MELA2022

MICCAI 2022 MELA Challenge: A Large-Scale Detection Benchmark of 1,100 CT Scans for Mediastinal Lesion Analysis

TDSC-ABUS2023

Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound

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.

MICCAI FLARE 2022

MICCAI 2022 Fast and Low-resource semi-supervised Abdominal oRgan sEgmentation (FLARE) Challenge

MICCAI HECKTOR 2022

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

K2S: from undersampled K-space To automatic Segmentation

K2S: from undersampled K-space To automatic Segmentation

FH-PS-AOP challenge

Fetal Head and Pubic Symphysis Segmentation Challenge

autoPET-II

Automated Lesion Segmentation in PET/CT - Domain Generalization

ARCADE-MICCAI2023