Extraction of the contours of left ventricular cavity, according with those traced by medical doctors, from left ventriculograms using a neural edge detector

摘要

In this paper, we have proposed a novel edge detector using a multilayer neural network, called the neural edge detector (NED), and a new contour-extraction method using the NED to extract the contours according with those traced by medical doctors. The NED is a supervised edge detector: through training the NED with a set of input images and desired edges, it acquires the function of a desired edge detector. The proposed contour-extraction method consists of (a) edge detection using the NED, (b) extraction of rough contours based on band-pass filtering, and (c) contour tracking based on the candidates for the contours synthesized from the edges detected by the NED and the rough contours. The experiments to extract the contours of left ventricular cavity from left ventriculograms were performed. By comparative evaluation with the conventional edge detectors, it has been shown that the NED has the highest performance. Through the experiments to evaluate the performance of contour extraction, the following has been demonstrated: The proposed method can extract the contours according with those traced by medical specialists; The performance of the proposed method is higher than that of the conventional method; The proposed method has the about same ability of medical specialists.