Lijia Wang1,2, Mengchao Pei1,
Noel C. F. Codella3, Jonathan W. Weinsaft2,4, Martin R.
Prince2, Yi Wang2,3
1Shanghai Key laboratory of
Magnetic Resonance, East China Normal University, Shanghai, China, People's
Republic of; 2Department of Radiology, Weill Medical College of
Cornell University, New York, NY, United States; 3Department of
Physiology, Biophysics, and Systems Biology, Weill Medical College of Cornell
Universi, New York, NY, United States; 4Department of
Medicine-Cardiology, Weill Medical College of Cornell University, New York,
NY, United States
To reduce the intra- & inter- variabilities of manual intervention in left ventricle (LV) segmentation, an algorithmic LV segmentation method is proposed to select apical and basal LV positions based on spatio-temporal continuity of LV area and shape, enabling segment the entire LV at all the cardiac phases. This algorithm was validated on short axis cine SSFP data from 38 patients with IRB approval and HIPAA compliance by comparing with manual tracing, showing promise for rapid and accurate LV segmentation in routine clinical cardiac MRI.
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