- Grand Challenge

Valentin Oreiller

voreillehevs

Switzerland
HES-SO Valais
Institute of Information Systems

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Member for 2 years, 7 months
1 challenge submissions

Activity Overview

VESSEL12

Challenge User

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

Decathlon

Challenge User

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

WSSS4LUAD

Challenge User

The WSSS4LUAD dataset contains over 10,000 patches of lung adenocarcinoma from whole slide images from Guangdong Provincial People's Hospital and TCGA with image-level annotations. The goal of this challenge is to perform semantic segmentation for differentiating three important types of tissues in the WSIs of lung adenocarcinoma, including cancerous epithelial region, cancerous stroma region and normal region. Paticipants have to use image-level annotations to give pixel-level prediction.

MICCAI HECKTOR 2022

Challenge Editor

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

Multi-site, Multi-Domain Airway Tree Modeling (ATM’22)

Challenge User

Airway segmentation is a crucial step for the analysis of pulmonary diseases including asthma, bronchiectasis, and emphysema. The accurate segmentation based on X-Ray computed tomography (CT) enables the quantitative measurements of airway dimensions and wall thickness, which can reveal the abnormality of patients with chronic obstructive pulmonary disease (COPD). Besides, the extraction of patient-specific airway models from CT images is required for navigatiisted surgery.