Combining snakes and active shape models for segmenting the human left ventricle in echocardiographic images

We propose a method for segmenting the human left ventricle (LV) in ultrasonic images, which is based on principles from both Active Shape Models (ASM) and Active Contour Models (ACM). Principal Component Analysis (PCA) is applied to a frequency-based shape representation of the LV thus eliminating the need for the difficult determination of corresponding landmarks. The average ventricular shape and the set of most significant shape variation modes are obtained from a training set. The LV boundaries in new images are found by placing an initial ACM (Snake) and allowing it to deform only according to the examined shape variations. A training set of 105 expert-segmented echocardiographic images was used. Improvements in the segmentation results were obtained especially in cases where the ventricular boundary was partly occluded by noise.