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Proceedings Paper

Computer-assisted ultrasonic tissue characterization of the heart
Author(s): Reinhard Berger; Evelin Lieback; Roland Hetzer
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Paper Abstract

In ultrasonic tissue characterization the small reflections originating from the scattering structures inside the tissue are analyzed. To obtain diagnostic performance for tissue characterization by means of analysis of echocardiographic images we use methods of mathematical texture analysis. We investigate whether myocardial changes effect the texture of ultrasonic images and if this could be described using quantitative texture analysis. The texture analysis was computed in a single window of an ultrasound image/sequence covering the inner myocardial septum. Parameters from gray level histogram, co-occurrence matrices, run length statistics and run difference, from power spectrum and fractal dimensions were investigated to provide satisfying and generalizable results for classification of the myocardium. A set of parameters that could discriminate between normal and pathological myocardium were extracted. The results of 142 biopsies were compared with those of texture analysis in echocardiograms of 106 patients suspected having myocarditis. Using the reduced set of parameters the best sensitivity was 89.0% and the specificity was 83.6%. Myocarditis is associated with echocardiographic texture alteration. Texture analysis with methods of digital image processing can reliably identify myocarditis. A suitable solution for a computer-assisted non- invasive support for the diagnosis and detection of myocarditis was found.

Paper Details

Date Published: 12 April 2000
PDF: 8 pages
Proc. SPIE 3982, Medical Imaging 2000: Ultrasonic Imaging and Signal Processing, (12 April 2000); doi: 10.1117/12.382235
Show Author Affiliations
Reinhard Berger, aviCOM Ltd. Co. (Germany)
Evelin Lieback, German Heart Institute Berlin (Germany)
Roland Hetzer, German Heart Institute Berlin (Germany)

Published in SPIE Proceedings Vol. 3982:
Medical Imaging 2000: Ultrasonic Imaging and Signal Processing
K. Kirk Shung; Michael F. Insana, Editor(s)

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