Cortical Surface Reconstruction from High-Resolution MR Brain Images.

Sergey Osechinskiy,Frithjof Kruggel

doi:10.1155/2012/870196

Sergey Osechinskiy, Frithjof Kruggel

Open Access

https://doi.org/10.1155/2012/870196

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Abstract

Reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, for example, in sulcal morphometry and in studies of cortical thickness. Existing cortical reconstruction approaches are typically optimized for standard resolution (~1 mm) data and are not directly applicable to higher resolution images. A new PDE-based method is presented for the automated cortical reconstruction that is computationally efficient and scales well with grid resolution, and thus is particularly suitable for high-resolution MR images with submillimeter voxel size. The method uses a mathematical model of a field in an inhomogeneous dielectric. This field mapping, similarly to a Laplacian mapping, has nice laminar properties in the cortical layer, and helps to identify the unresolved boundaries between cortical banks in narrow sulci. The pial cortical surface is reconstructed by advection along the field gradient as a geometric deformable model constrained by topology-preserving level set approach. The method's performance is illustrated on exvivo images with 0.25–0.35 mm isotropic voxels. The method is further evaluated by cross-comparison with results of the FreeSurfer software on standard resolution data sets from the OASIS database featuring pairs of repeated scans for 20 healthy young subjects.

Highlights

The derivation of a computerized representation of the cerebral cortical layer based on threedimensional (3D) magnetic resonance (MR) images of the brain, is an important step in quantitative analysis of the human brain structure, for example, in the analysis of cortical folding patterns, in brain morphometry, and in cortical thickness studies
Designated dielectric layer field mapping, or DELFMAP, for the automated reconstruction of the cortical compartment from MR images, which is based on several partial differential equation (PDE) modeling stages
Test images simulate a simplified 3D geometry of a sulcal fold and contain two white matter (WM) stalks separated by the sulcal space; the WM is covered by a layer of gray matter (GM) having unequal thickness at the opposing banks and a smoothly varying thickness at the fundus (Figure 4(a))

Summary

Introduction

The derivation of a computerized representation of the cerebral cortical layer based on threedimensional (3D) magnetic resonance (MR) images of the brain, is an important step in quantitative analysis of the human brain structure, for example, in the analysis of cortical folding patterns, in brain morphometry, and in cortical thickness studies. The cerebral cortex, considered at the spatial scale of MR images, is a thin layer of neural tissue, called gray matter (GM), located on the outer side of the white matter (WM), and surrounded by the cerebrospinal fluid (CSF). The opposite banks of gray matter in deep sulci are not always resolved as separate and can appear as fused together (Figure 1), leading to invalid models of the cortical layer and propagating errors further into quantitative measurements (e.g., cortical thickness). This may present a particular challenge for an automated reconstruction algorithm, requiring specific means for an automatic detection and correction of topologically and geometrically problematic cases

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