Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments

Author

Toumoulin, Christine ; Boldak, Cezary ; Dillenseger, Jean Louis ; Coatrieux, Jean Louis ; Rolland, Yan

Author_Institution

Lab. Traitement du Signal et de l´´Image, Rennes I Univ., France

Volume

48

Issue

5

fYear

2001

fDate

5/1/2001 12:00:00 AM

Firstpage

604

Lastpage

606

Abstract

An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.

Keywords

blood vessels; computational geometry; computerised tomography; image segmentation; medical image processing; method of moments; 3D segmentation; adaptive control; background intensity levels; geometrical moments; local cylindrical approximation; lower limb arteries; multidetector computed tomography scanner; robust estimation; three-dimensional imaging; very fast algorithm; very large 3D data sets; vessel diameter; vessel intensity levels; vessel tracking; vessels extraction; window centering; Adaptive control; Algorithm design and analysis; Angiography; Arteries; Computed tomography; Data mining; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Robust control; Algorithms; Artifacts; Data Display; Femoral Artery; Humans; Ischemia; Leg; Models, Cardiovascular; Popliteal Artery; Radiographic Image Enhancement; Thrombosis; Tomography, X-Ray Computed;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/10.918601

Filename

918601