LEFT-VENTRICLE BOUNDARY DETECTION FROM NUCLEAR-MEDICINE IMAGES

We present here a new algorithm for segmentation of nuclear medicine i mages to detect the left-ventricle (LV)boundary, tn this article,ther image segmentation techniques, such as edge detection and region growi ng, are also compared and evaluated. In the edge detection approach, w e explored the relation ship between the LV boundary characteristics i n nuclear medicine images and their radial orientations: we observed t hat no single brightness function leg, maximum of first or second deri vative) is sufficient to identify the boundary in every direction, in the region growing approach, several criteria, including intensity cha nge, gradient magnitude change, gradient direction change, and running mean differences, were tested. We found that none of these criteria a lone was sufficient to successfully detect the LV boundary. then we pr oposed a simple but successful region growing method-Contour-Modified Region Growing (CMRG). CMRG is an easy-to-use, robust, and rapid image segmentation procedure. Based on our experiments, this method seems t o perform quite well in comparison to other automated methods that we have tested because of its ability to handle the problems of both low signal-to-noise (SNR) as well as low image contrast without any assump tions about the shape of the left ventricle. Copyright (C) 1998 by W.B . Saunders Company.