Segmentation of the pulmonary vascular tree

Author

Prieto, J.-C. ; Revol-Muller, C. ; Odet, C. ; Orkisz, Michal ; Romanello, C.P. ; Romanello, V.P. ; Hoyos, M.H.

Author_Institution

CREATIS, Univ. de Lyon, Villeurbanne, France

fYear

2012

fDate

1-5 Oct. 2012

Firstpage

1

Lastpage

7

Abstract

A method to semi-automatically segment the pulmonary vascular tree from computed axial tomography (CAT) images is presented. The main goal is to aid the diagnosis and treatment of acute respiratory distress syndrome and pulmonary embolism. The proposed methodology is based on a variational region growing method and a multi-scale vessel enhancement filter. Preliminary studies were made with a 20 CAT image dataset that included healthy and pathological lung scans. The results were satisfactory, although in some cases vessels were not correctly distinguished from other thin structures such as mucus-filled bronchi, nodules and airway walls connected to vessels.

Keywords

Hessian matrices; computerised tomography; medical image processing; patient diagnosis; patient treatment; trees (mathematics); CAT image dataset; Hessian matrix; acute respiratory distress syndrome; computed axial tomography images; image segmentation; multi-scale vessel enhancement filter; pathological lung scans; pulmonary embolism; pulmonary vascular tree; variational region growing method; Biomedical imaging; Image color analysis; Image segmentation; Lungs; Pathology; Silicon compounds; Tomography; hessian matrix; pulmonary vascular tree; segmentation; vesselness;

fLanguage

English

Publisher

ieee

Conference_Titel

Informatica (CLEI), 2012 XXXVIII Conferencia Latinoamericana En

Conference_Location

Medellin

Print_ISBN

978-1-4673-0794-9

Type

conf

DOI

10.1109/CLEI.2012.6427119

Filename

6427119