Abstract:
Automatic identification of endocardial and epicardial
boundaries of LV has been a focus of research attention in
the development of computational methods and computer
support for cardiologists in identifying clinical heart
disease and their diagnosis. Among heart imaging
techniques, echocardiography offers significant
advantages because of its low cost, portability, minimal
discomfort, the absence of ionizing radiation, and its
possible application for patient monitoring through real
time processing. However, images generated from
echocardiogram data are of poor quality. This paper
presents the initial work in the development of a data
mining approach for computer-assisted detection of
myocardial ischemia, which includes Left Ventricle (LV)
wall boundary identification, segmentation and further
comparative analysis of wall segments in pre- and post
stress echocardiograms.
