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Abstract #2871

Deep-learning cardiac MRI for quantitative assessment of ventricular volumes

Yifan Qi1, Fusheng Wang1, J. Jane Cao2, and Yulee Li2
1Computer Science, Stony Brook University, Stony Brook, NY, United States, 2St. Francis Hospital, DeMatteis Center for Cardiac Research and Education, Greenville, NY, United States

The presented work introduces a deep-learning cardiac MRI approach to quantitative assessment of ventricular volumes from raw MRI data without image reconstruction. As the information required for volumetric measurements is less than that for image reconstruction, ventricular function may be assessed with less MRI data than conventional image-based methods. This offers the potential to improve temporal resolution for quantitatively imaging cardiac function.

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