Shape Restoration of the Left Ventricle

Authors: May-Ling Tan, Yi Su, Chi-Wan Lim, Liang Zhong, Ru-San Tan

Abstract:

This paper describes an automatic algorithm to restore the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data using a geometry-driven optimization approach. Our basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration. A geometrical measure known as the Minimum Principle Curvature (κ2) is used to assess the smoothness of the LV. This measure is used to construct the objective function of a two-step optimization process. The objective of the optimization is to achieve a smooth epicardial shape by iterative in-plane translation of the MRI slices. Quantitatively, this yields a minimum sum in terms of the magnitude of κ 2, when κ2 is negative. A limited memory quasi-Newton algorithm, L-BFGS-B, is used to solve the optimization problem. We tested our algorithm on an in vitro theoretical LV model and 10 in vivo patient-specific models which contain significant motion artifacts. The results show that our method is able to automatically restore the shape of LV models back to smoothness without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings.

Keywords: Magnetic Resonance Imaging, Left Ventricle, ShapeRestoration, Principle Curvature, Optimization

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334229

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