- Grand Challenge

Lorenz Berger

lungster

United Kingdom
UCL
TIG

Statistics

Member for 7 years, 11 months

Activity Overview

ANODE09

Challenge User

ANODE09 is an initiative to compare systems that perform automatic detection of pulmonary nodules in chest CT scans on a single common database, with a single evaluation protocol.

LOLA11

Challenge User

The goal of LOLA11 (LObe and Lung Analysis 2011) is to compare methods for (semi-)automatic segmentation of the lungs and lobes from chest computed tomography scans. Any team, whether from academia or industry, can join.

LUNA16

Challenge User

The LUNA16 challenge: automatic nodule detection on chest CT

Diabetic Foot Ulcer Challenge 2020

Challenge User

Diabetic Foot Ulcer Challenge 2020

AutoImplant

Challenge User

the MICCAI 2020 Cranial Implant Design Challenge

Parse2022

Challenge User

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.