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Proceedings Paper

IVUS-based histology of atherosclerotic plaques: improving longitudinal resolution
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Paper Abstract

Although Virtual Histology (VH) is the in-vivo gold standard for atherosclerosis plaque characterization in IVUS images, it suffers from a poor longitudinal resolution due to ECG-gating. In this paper, we propose an image-based approach to overcome this limitation. Since each tissue have different echogenic characteristics, they show in IVUS images different local frequency components. By using Redundant Wavelet Packet Transform (RWPT), IVUS images are decomposed in multiple sub-band images. To encode the textural statistics of each resulting image, run-length features are extracted from the neighborhood centered on each pixel. To provide the best discrimination power according to these features, relevant sub-bands are selected by using Local Discriminant Bases (LDB) algorithm in combination with Fisher's criterion. A structure of weighted multi-class SVM permits the classification of the extracted feature vectors into three tissue classes, namely fibro-fatty, necrotic core and dense calcified tissues. Results shows the superiority of our approach with an overall accuracy of 72% in comparison to methods based on Local Binary Pattern and Co-occurrence, which respectively give accuracy rates of 70% and 71%.

Paper Details

Date Published: 12 March 2010
PDF: 7 pages
Proc. SPIE 7629, Medical Imaging 2010: Ultrasonic Imaging, Tomography, and Therapy, 76290Y (12 March 2010); doi: 10.1117/12.843791
Show Author Affiliations
Arash Taki, Technische Univ. München (Germany)
Olivier Pauly, Univ. of Tehran (Iran, Islamic Republic of)
S. Kamaledin Setarehdan, Sabanci Univ. (Turkey)
Gozde Unal, Technische Univ. München (Germany)
Nassir Navab, Technische Univ. München (Germany)

Published in SPIE Proceedings Vol. 7629:
Medical Imaging 2010: Ultrasonic Imaging, Tomography, and Therapy
Jan D'hooge; Stephen A. McAleavey, Editor(s)

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