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Texture-Driven Coronary Artery Plaque Characterization Using Wavelet Packet Signatures

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

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.


More About This Work

Academic Units
Biomedical Engineering
Published Here
August 12, 2010


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.

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