An Intensity Based Statistical Approach for Left Ventricular Localization and Identification of End-Systolic and End-Diastolic Images from Cine Cardiac MRI

Sotirios Athanasios Tsaftaris¹, Xiangzhi Zhou², Richard Tang², Rachel Klein², Rohan Dharmakumar²

A critical component in computing quantitative diagnostic metrics, such as ejection fraction, as well as image segmentation and registration, is the accurate identification of the end-systolic (ES) and end-diastolic (ED) frames in cine MRI. Localization of the LV is also important, to assist further analysis (ie., myocardial segmentation). In this paper we propose an image-driven statistical method that utilizes cross-correlation of pixels, to detect ES and ED images, as well as, localize the LV, from cine MRI acquired from canines under control conditions. The method is fully automated, computationally efficient, and requires no parameterization, initialization, and ROI selection.robust, and can be extended to 4D MRI.