Cortical Surface Reconstruction from High-Resolution MR Brain Images
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 stand...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2012/870196 |
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| author | Sergey Osechinskiy Frithjof Kruggel |
| author_facet | Sergey Osechinskiy Frithjof Kruggel |
| author_sort | Sergey Osechinskiy |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c10b04ff435244b184c1f90a92e883d4 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-c10b04ff435244b184c1f90a92e883d42025-02-03T01:10:22ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962012-01-01201210.1155/2012/870196870196Cortical Surface Reconstruction from High-Resolution MR Brain ImagesSergey Osechinskiy0Frithjof Kruggel1Department of Biomedical Engineering, University of California, Irvine, CA 92697, USADepartment of Biomedical Engineering, University of California, Irvine, CA 92697, USAReconstruction 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.http://dx.doi.org/10.1155/2012/870196 |
| spellingShingle | Sergey Osechinskiy Frithjof Kruggel Cortical Surface Reconstruction from High-Resolution MR Brain Images International Journal of Biomedical Imaging |
| title | Cortical Surface Reconstruction from High-Resolution MR Brain Images |
| title_full | Cortical Surface Reconstruction from High-Resolution MR Brain Images |
| title_fullStr | Cortical Surface Reconstruction from High-Resolution MR Brain Images |
| title_full_unstemmed | Cortical Surface Reconstruction from High-Resolution MR Brain Images |
| title_short | Cortical Surface Reconstruction from High-Resolution MR Brain Images |
| title_sort | cortical surface reconstruction from high resolution mr brain images |
| url | http://dx.doi.org/10.1155/2012/870196 |
| work_keys_str_mv | AT sergeyosechinskiy corticalsurfacereconstructionfromhighresolutionmrbrainimages AT frithjofkruggel corticalsurfacereconstructionfromhighresolutionmrbrainimages |