Title:

Texture-Driven Coronary Artery Plaque Characterization Using Wavelet Packet Signatures

Author(s):

Katouzian, Amin
Baseri, Babak
Konofagou, Elisa E.
Laine, Andrew F.

Date:

2008

Type:

Articles

Department:

Biomedical Engineering

Permanent URL:

http://hdl.handle.net/10022/AC:P:9449

Notes:

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro: Proceedings: May 14-17, 2008, Paris Marriott Rive Gauche Hotel & Conference Center, Paris, France (Piscataway, N.J.: IEEE, 2008), pp. 197-200.

Abstract:

High-frequency ultrasound transducers are being widely used to generate high resolution, real time, cross-sectional images of the coronary arteries. In this paper, we present a robust unsupervised texture-derived technique based on multi-channel wavelet frames to delineate atherosclerotic plaque compositions. The intravascular ultrasound (IVUS) signals were acquired from coronary arteries dissected from 32 diseased cadaver hearts employing 40 MHz mechanically rotating, single-element transducers. The wavelet packet representations were classified using a K- means clustering algorithm to generate IVUS-histology color maps (IV-HCMs) and categorize tissues in lipidic, fibrotic and calcified. Finally, two independent observers evaluated the results contrasting the histology images corresponding to the IV-HCMs. Our results show that the proposed algorithm may have great potential as an alternative to existing spectrum-based classification techniques.

Subject(s):

Biomedical engineering

DOI:

http://dx.doi.org/10.1109/ISBI.2008.4540966

Item views:

240

Metadata:

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