Left Ventricular Contour Detection With A Dynamic Search Algorithm

Publisher Website
Google Scholar
Abstract
A new method is described for the automated detection of left ventricular (LV) contours in contrast cineangiograms in the RAO projection. The method requires the manual definition of three reference points, two at the aortic valve and one at the apex. Next, a model, derived from a learning set of manually drawn contours, is fit through these points and edge features are extracted along scanlines perpendicular to the local model boundary direction. The edge detection method is based on dynamic programming techniques, thus allowing the determination of local contour points to be influenced by the entire global border path. A preliminary qualitative evaluation study showed that in 85-90% of the ED-frames and in 70-80% of the ES-frames the LV boundary could be detected fully automatic. The time required to detect an ED- or ES-contour in a 512x512 image is 10 seconds. On the basis of these preliminary data it may be concluded that reliable automated detection of LV-boundaries in a routinely acceptable processing time is feasible.© (1987) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This publication has 0 references indexed in Scilit: