A Novel Automated Left Ventricle Segmentation Routine
In this paper we present a system for the automatic segmentation of the left ventricle (LV) of the heart from breath hold MRI images with subsequent ejection fraction (EF) calculations. The ventricular luminal contours in short and long-axis slices are enhanced with morphological image processing methods and extracted using a novel Global Optimal Closed Path algorithm. In this study, contours both including and excluding LV trabeculations and papillary muscles are considered. Ventricular 3D-reconstructions are based on the use of both short-axis and long-axis contours, with the long-axis contours also being used as an internal skeleton template of the LV to correct for through plane motion. A series of volumes of the reconstructed 3D ventricle is evaluated at different times during the cycle and the EF calculated. By comparing our numerical results with those derived from manual segmentations on eight normal subjects, we conclude that the automated system performance is reliable and consistent.