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Proceedings Paper

An automated pipeline for cortical surface generation and registration of the cerebral cortex
Author(s): Wen Li; Luis Ibanez; Arnaud Gelas; B. T. Thomas Yeo; Marc Niethammer; Nancy C. Andreasen; Vincent A. Magnotta
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Paper Abstract

The human cerebral cortex is one of the most complicated structures in the body. It has a highly convoluted structure with much of the cortical sheet buried in sulci. Based on cytoarchitectural and functional imaging studies, it is possible to segment the cerebral cortex into several subregions. While it is only possible to differentiate the true anatomical subregions based on cytoarchitecture, the surface morphometry aligns closely with the underlying cytoarchitecture and provides features that allow the surface of the cortex to be parcellated based on the sulcal and gyral patterns that are readily visible on the MR images. We have developed a fully automated pipeline for the generation and registration of cortical surfaces in the spherical domain. The pipeline initiates with the BRAINS AutoWorkup pipeline. Subsequently, topology correction and surface generation is performed to generate a genus zero surface and mapped to a sphere. Several surface features are then calculated to drive the registration between the atlas surface and other datasets. A spherical diffeomorphic demons algorithm is used to co-register an atlas surface onto a subject surface. A lobar based atlas of the cerebral cortex was created from a manual parcellation of the cortex. The atlas surface was then co-registered to five additional subjects using a spherical diffeomorphic demons algorithm. The labels from the atlas surface were warped on the subject surface and compared to the manual raters. The average Dice overlap index was 0.89 across all regions.

Paper Details

Date Published: 12 March 2011
PDF: 7 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796229 (12 March 2011); doi: 10.1117/12.876509
Show Author Affiliations
Wen Li, Univ. of Iowa (United States)
Luis Ibanez, Kitware, Inc. (United States)
Arnaud Gelas, Harvard Medical School (United States)
B. T. Thomas Yeo, Harvard Univ. (United States)
Marc Niethammer, Univ. of North Carolina at Chapel Hill (United States)
Nancy C. Andreasen, The Univ. of Iowa (United States)
Vincent A. Magnotta, The Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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