Meeting Banner
Abstract #2629

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

Yuhua Chen1,2, Jianing Pang2, David Neiman2,3, 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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here