Fully automatic segmentation of left ventricular anatomy in 3-D LGE-MRI.

Abstract

The current challenge for electrophysiology procedures, targeting the left ventricle, is the localization and qualification of myocardial scar. Late gadolinium enhanced magnetic resonance imaging (LGE-MRI) is the current gold standard to visualize regions of myocardial infarction. Commonly, a stack of 2-D images is acquired of the left ventricle in short-axis orientation. Recently, 3-D LGE-MRI methods were proposed that continuously cover the whole heart with a high resolution within a single acquisition. The acquisition promises an accurate quantification of the myocardium to the extent of myocardial scarring. The major challenge arises in the analysis of the resulting images, as the accurate segmentation of the myocardium is a requirement for a precise scar tissue quantification. In this work, we propose a novel approach for fully automatic left ventricle segmentation in 3-D whole-heart LGE-MRI, to address this limitation. First, a two-step registration is performed to initialize the left ventricle. In the next step, the principal components are computed and a pseudo short axis view of the left ventricle is estimated. The refinement of the endocardium and epicardium is performed in polar space. Prior knowledge for shape and inter-slice smoothness is used during segmentation. The proposed method was evaluated on 30 clinical 3-D LGE-MRI datasets from individual patients obtained at two different clinical sites and were compared to gold standard segmentations of two clinical experts. This comparison resulted in a Dice coefficient of 0.83 for the endocardium and 0.80 for the epicardium.

• Authors: Tanja Kurzendorfer, Christoph Forman, Michaela Schmidt, Christoph Tillmanns, Andreas Maier, Alexander Brost
• Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society (Comput Med Imaging Graph) Vol. 59 Pg. 13-27 (Jul 2017) ISSN: 1879-0771 [Electronic] United States
• PMID: 28527317 (Publication Type: Journal Article)
• Copyright: Copyright © 2017 Elsevier Ltd. All rights reserved.

Chemical References

• Gadolinium

Topics

• Gadolinium
• Heart Ventricles
• Humans
• Imaging, Three-Dimensional
• Magnetic Resonance Imaging