Semiautomatic contour detection in ultrasound M-mode images.

Abstract We have developed a method for semiautomatic contour detection in M-mode images. The method combines tissue Doppler and grey-scale data. It was used to detect: 1. the left endocardium of the septum, the endocardium and epicardium of the posterior wall in 16 left ventricular short-axis M-modes, and 2. the mitral ring in 38 anatomical M-modes extracted pair-wise in 19 apical four-chamber cine-loops (healthy subjects). We validated the results by comparing the computer-generated contours with contours manually outlined by four echocardiographers. For all boundaries, the average distance between the computer-generated contours and the manual outlines was smaller than the average distance between the manual outlines. We also calculated left ventricular wall thickness and diameter at end-diastole and end-systole and lateral and septal mitral ring excursions, and found, on average, clinically negligible differences between the computer-generated indices and the same indices based on manual outlines (0.8–1.8 mm). The results were also within published normal values. In conclusion, this initial study showed that it was feasible in a robust and efficient manner to detect continuous wall boundaries in M-mode images so that tracings of left ventricular wall thickness, diameter and long axis could be derived.