APPLICATION OF AUTOMATIC BOUNDARY DETECTION FOR COMPUTERIZED QUANTITATIVE-ANALYSIS OF LEFT-VENTRICULAR REGIONAL WALL-MOTION BY 2-DIMENSIONAL ECHOCARDIOGRAPHY

This study was designed to set up a computer-aided image processing al gorithm for boundary detection from two-dimensional echocardiography a nd to establish a computerized model for quantitative analysis of left ventricular wall motion with the application of automatic boundary de tection. The four-chamber view echocardiographic images of seven norma l subjects and five patients with acute myocardial infarction were inv estigated. The main steps of image processing in this algorithm includ ed automatic threshold estimation, contrast stretching, radial search of endocardial boundary, and smoothing of the boundary. The displaceme nts of the left ventricular endocardial contour from end-diastolic to end-systolic frame were measured using a sample point connection model . For analysis of the regional contraction, the left ventricular endoc ardial contour was divided equally into six segments. The wall motion curves in patients were compared with the normal wall motion pattern e stablished from the normal subjects to identify the segments with norm al or abnormal wall motion. The results of this quantitative method we re compared with those of qualitative analysis. In the 30 segments of the five patients, quantitative analysis correctly identified nine of the II segments with abnormal wall motion diagnosed by qualitative ana lysis (sensitivity, 82%) and identified 17 of the 19 segments with nor mal wall motion (specificity, 89%). The positive and negative predicti ve values of quantitative analysis were 82% (9 of 11) and 89% (17 of 1 9), respectively, and the diagnostic accuracy was 87% (26 of 30). Our preliminary results suggest that computer-aided boundary detection can be applied to establish an objective and useful model for quantitativ e analysis of left ventricular regional wall motion.