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Abstract #4764

A Novel 4D Semi-automatic Segmentation Algorithm for Whole-heart 3D Cine Magnetic Resonance Imaging

Ruizhi Liao1, Danielle F. Pace1, Andrew J. Powell2, Polina Golland1, and Mehdi Hedjazi Moghari2

1Massachusetts Institute of Technology, Cambridge, MA, United States, 2Boston Children's Hospital, Boston, MA, United States

Three-dimensional (3D) time-resolved (cine) whole-heart magnetic resonance imaging promises to greatly facilitate comprehensive and evaluation of cardiac function and morphology. We present here a robust semi-automatic 4D segmentation algorithm, using patch-based volumetric segmentation and a temporal image registration method, to reduce the segmentation time of 3D cine datasets to less than 30 minutes and to enable wide clinical use. Resulting volumetric measurements of the left ventricle and right ventricle are aligned with measurements from the current clinical routine. By visualizing the anatomy and dynamics of the heart, we show that 3D cine datasets promise to enhance surgical planning for patients with complex congenital heart disease.

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