Left Ventricle Segmentation in Cardiac MRI Images

Abstract

Imaging of the left ventricle using cine short-axis MRI sequences, considered as an important tool that used for evaluating cardiac function by calculating different cardiac parameters. The manual segmentation of the left ventricle in all image sequences takes a lot of time, and therefore the automatic segmentation of the left ventricle is main step in cardiac function evaluation. In this paper, we proposed an automatic method for segmenting the left ventricle in cardiac MRI images. We applied pixel classification method by using number of features and KNN classifier for segmenting the left ventricle Cavity, and from its output we can get the endocardial contour. Then, we transformed image pixels from Cartesian to polar coordinates for segmenting the epicardial contour. This method was tested on large number of images, and we achieved good results reached to 95.61% sensitivity, and 98.9% specificity for endocardium segmentation, and 93.32% sensitivity, and 98.49% specificity for epicardium segmentation. The results of the proposed method show the availability for fast and reliable segmentation of the left ventricle.