Abstract #2629

Automatic Ventricular Function Measurement with Free-breathing Self-Gated 4D Whole-Heart Cardiac MRI

Yuhua Chen^1,2, Jianing Pang², David Neiman^2,3, Yibin Xie², Christopher T. Nguyen², Zhengwei Zhou², and Debiao Li²

¹Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States, ²Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, ³Electrical Engineering, University of Wisconsin, Madison, WI, United States

Measuring left ventricle (LV) function using MRI currently involves a highly user-dependent and labor-intensive workflow, which includes manual segmentation of 2D cine images acquired during patient breath-hold at multiple short axis locations. In this work, we propose a fully automated LV segmentation method based on a recently developed free-breathing, self-gated 4D whole-heart imaging technique and multi-atlas label fusion, which enables streamlined, “push-button” LV function assessment. We performed cross validation study on five healthy subjects where the proposed method was shown to offer consistent results with manual labelling.

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