Left ventricle automated detection method in gated isotopic ventriculography using fuzzy clustering

Abstract

A method that uses the fuzzy ISODATA clustering algorithm and Fourier analysis is proposed for automated detection of heart left ventricle contours. This operation is used for quantitative analysis of cardiac function. The computation begins by finding the phase image. The fuzzy ISODATA algorithm is first applied to this image to generate a number of clusters that correspond to the organ substructures (ventricles, atria). Second, the ventricles cluster is isolated and the intensities of its points are replaced by the corresponding ones from the original (end diastolic) frame. Finally, a reduced image representing the ventricular region is obtained and an additional clustering is performed to find the left ventricular boundary automatically. This algorithm is tested by application of 105 sets of 16 images each. These results are compared with the measurements obtained with two semi-automatic methods used, respectively, on the Philips and the Sopha Medical gamma cameras.