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Proceedings Paper

Visualization of myocardial perfusion defects in single photon emission computerized (SPECT) studies
Author(s): L. Jarrett Malone; James R. Zeidler; Walter H. Ku; David W. Yeung
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Paper Abstract

In this paper, we present a semi-automatic technique to quantize and to visualize myocardial perfusion defects volumetrically. This involves: (1) differentiating the myocardium from encroaching viscera, (2) determining the mass of myocardium, (3) locating and measuring the perfusion defects, and (4) graphically rendering them. First, to differentiate between myocardium and other thoracic structures, we introduce the concept of Maximum Intensity Surface Segmentation (MISS). By locating local maximums in our cardiac Single Photon Emission Computerized Tomography (SPECT) image and connecting ones sufficiently close together, we generate the basic shape of the myocardium and the encroaching ones sufficiently close together, we generate the basic shape of the myocardium and the encroaching structures. Second, with the shape of the myocardium determined, we then measure the thickness at each point of the heart wall. Fitting bicubic splines to the measured myocardial thicknesses, we create smooth epicardial and endocardial boundaries for both normal and abnormal regions. Third, using a thresholding technique based on the maximal myocardial activity, we determine the abnormal regions. Finally, with the abnormal regions and the myocardial mass determined, we can calculate the abnormality's size as a percentage of the total myocardial mass. By providing quantitative measurements, our technique meets the physician's long standing need for a volumetric quantitation of the size of myocardial perfusion abnormalities.

Paper Details

Date Published: 9 September 1994
PDF: 9 pages
Proc. SPIE 2359, Visualization in Biomedical Computing 1994, (9 September 1994); doi: 10.1117/12.185233
Show Author Affiliations
L. Jarrett Malone, Univ. of California/San Diego (United States)
James R. Zeidler, Univ. of California/San Diego and Naval Command, Control and Ocean Surveillance Ctr. (United States)
Walter H. Ku, Univ. of California/San Diego (United States)
David W. Yeung, Veterans Affairs Medical Ctr. and Univ. of California/San Diego School of Medicine (United States)


Published in SPIE Proceedings Vol. 2359:
Visualization in Biomedical Computing 1994
Richard A. Robb, Editor(s)

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