Fast and Robust Localization of the Heart in Cardiac MRI Series - a Cascade of Operations for Automatically Detecting the Heart in Cine MRI Series

This work presents a robust approach for fast initialization of an Active Appearance Model for subsequent segmentation of cardiac MRI data. The method automatically determines AAM initialization parameters: position, orientation, and scaling of the model. Four steps are carried out: (1) variance images over time are calculated to find a bounding box that roughly defines the heart region; (2) circle Hough-transformation adapted to gray values is performed to detect the left ventricle; (3) thresholding is carried out to determine the orientation of the heart; (4) the optimal initialization is selected using a mean texture model. The method was evaluated on 42 MRI short axis studies coming from two MRI scanners of two different vendors. Automatic initializations are compared to manual ones. It is shown that the proposed automatic method is much faster than and achieves results qualitatively equal to manual initialization.