RESEARCH ARTICLE


Texture Analysis and Radial Basis Function Approximation for IVUS Image Segmentation



Papadogiorgaki Maria 1, Mezaris Vasileios 1, Chatzizisis Yiannis S2, *, Giannoglou George D2, Kompatsiaris Ioannis 1
1 Informatics and Telematics Institute, Centre for Research and Technology Hellas, 1st Km Thermi-Panorama Rd, P.O. Box 60361, GR-57001 Thermi-Thessaloniki, Greece
2 Cardiovascular Engineering and Atherosclerosis Laboratory, AHEPA University Hospital, Aristotle University Medi-cal School, GR-54636, Thessaloniki, Greece


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Creative Commons License
2008 Bentham Science Publishers Ltd.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestrictive use, distribution, and reproduction in any medium, provided the original work is properly cited.

* Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA; Tel: 617 525 7745; Fax: 617 734 1874; E-mailjoc@med.auth.gr


Abstract

>Intravascular ultrasound (IVUS) has become in the last years an important tool in both clinical and research applications. The detection of lumen and media-adventitia borders in IVUS images represents a first necessary step in the utilization of the IVUS data for the 3D reconstruction of human coronary arteries and the reliable quantitative assessment of the atherosclerotic lesions. To serve this goal, a fully automated technique for the detection of lumen and media-adventitia boundaries has been developed. This comprises two different steps for contour initialization, one for each corresponding contour of interest, based on the results of texture analysis, and a procedure for approximating the initialization results with smooth continuous curves. A multilevel Discrete Wavelet Frames decomposition is used for texture analysis, whereas Radial Basis Function approximation is employed for producing smooth contours. The proposed method shows promising results compared to a previous approach for texture-based IVUS image analysis.

Keywords: Intravascular ultrasound, coronary arteries, image segmentation, lumen, media, adventitia, boundaries, texture analysis. .