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Abstract #3715

Unsupervised and Reproducible Image-Based Identification of Cardiac Phases in Cine SSFP MRI

Sotirios A. Tsaftaris1,2, Xiangzhi Zhou2, Richard Tang2, Rohan Dharmakumar2

1Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, United States; 2Radiology, Northwestern University, Chicago, IL, United States

It is particularly important for the evaluation of cardiac phase-resolved myocardial blood-oxygen-level-dependent (BOLD) MRI studies, to robustly and reproducibly identify end-systolic (ES) and end-diastolic (ED). Most automated methods rely on identifying the minimum and maximum of the blood pool area in the Left Ventricle chamber, but they are computationally intensive, susceptible to noise, and require prior localization and segmentation of the chamber. The purpose of this work is to develop automated methods to facilitate in the robust and reproducible evaluation of cardiac phase-resolved myocardial BOLD MRI through identification of ES and ED images.