Generation of Myocardial Wall Surface Meshes from Segmented MRI

Oskar Škrinjar,Arnaud Bistoquet

doi:10.1155/2009/313517

Oskar Škrinjar, Arnaud Bistoquet

Open Access

https://doi.org/10.1155/2009/313517

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Abstract

This paper presents a novel method for the generation of myocardial wall surface meshes from segmented 3D MR images, which typically have strongly anisotropic voxels. The method maps a premeshed sphere to the surface of the segmented object. The mapping is defined by the gradient field of the solution of the Laplace equation between the sphere and the surface of the object. The same algorithm is independently used to generate the surface meshes of the epicardium and endocardium of the four cardiac chambers. The generated meshes are smooth despite the strong voxel anisotropy, which is not the case for the marching cubes and related methods. While the proposed method generates more regular mesh triangles than the marching cubes and allows for a complete control of the number of triangles, the generated meshes are still close to the ones obtained by the marching cubes. The method was tested on 3D short-axis cardiac MR images with strongly anisotropic voxels in the long-axis direction. For the five tested subjects, the average in-slice distance between the meshes generated by the proposed method and by the marching cubes was 0.4 mm.

Highlights

Surface models of the epicardium and endocardium of the heart chambers are used in a number of biomedical applications for visualization [1], virtual reality [2], segmentation [3, 4], motion analysis [5, 6], shape analysis [7, 8], and modeling [9, 10] purposes
For each segmented object we construct its surface in implicit form and map the mesh from the sphere to the surface using the gradient field of the solution of the Laplace equation between the surface and the sphere
In this paper we present a method for generation of myocardial wall surface meshes from segmented MRI

Summary

Introduction

Surface models of the epicardium and endocardium of the heart chambers are used in a number of biomedical applications for visualization [1], virtual reality [2], segmentation [3, 4], motion analysis [5, 6], shape analysis [7, 8], and modeling [9, 10] purposes. An alternative way to use the marching cubes is to first construct an implicit surface from the segmented image, and apply the marching cubes to the scalar field (the implicit surface is the zero level set of the scalar field) on a uniformly sampled image domain [18]. This way one can control the size of the mesh triangles

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