- Grand Challenge

Fawzia Amri

amrif1

United States of America
University of Dayton
Electrical and Computer Engineering
Website

Statistics

Member for 3 years

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.

QUBIQ2021

Challenge User

Quantification of Uncertainties in Biomedical Image Segmentation Challenge 2021

AIROGS

Challenge User

Artificial Intelligence for RObust Glaucoma Screening 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.