Ms. Wen Li Profile

Wen Li

PhD Candidate at Univ of Iowa

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Proceedings Article | 12 March 2011 Paper

An automated pipeline for cortical surface generation and registration of the cerebral cortex

Wen Li, Luis Ibanez, Arnaud Gelas, B. T. Thomas Yeo, Marc Niethammer, Nancy Andreasen, Vincent Magnotta

Proceedings Volume 7962, 796229 (2011) https://doi.org/10.1117/12.876509

KEYWORDS: Optical spheres, Cerebral cortex, Spherical lenses, Magnetic resonance imaging, Brain, Tissues, Image registration, Natural surfaces, Neuroimaging, Image segmentation

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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.

Proceedings Article | 13 March 2009 Paper

Evaluation of topology correction methods for the generation of the cortical surface

Wen Li, Vincent Magnotta

Proceedings Volume 7261, 726132 (2009) https://doi.org/10.1117/12.812323

KEYWORDS: Brain, Tissues, Magnetic resonance imaging, Neuroimaging, Natural surfaces, 3D image processing, Cerebral cortex, Optical spheres, Visualization, Image segmentation

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The cerebral cortex is a highly convoluted anatomical structure. The folding pattern defined by sulci and gyri is a complex pattern that is very heterogeneous across subjects. The heterogeneity across subjects has made the automated labeling of this structure into its constituent components a challenge to the field of neuroimaging. One way to approach this problem is to conformally map the surface to another representation such as a plane or sphere. Conformal mapping of the surface requires that surface to be topologically correct. However, noise and partial volume artifacts in the MR images frequently cause holes or handles to exist in the surface that must be removed. Topology correction techniques have been proposed that operate on the cortical surface, the original image data, and hybrid methods have been proposed. This paper presents an experimental assessment of two different topology correction methods. The first approach is based on modification of 3D voxel data. The second method is a hybrid approach that determines the location of defects from the surface representation while repairing the surface by modifying the underlying image data. These methods have been applied to 10 brains, and a comparison is made among them. In addition, detailed statistics are given based on the voxel correction method. Based on these 10 MRI datasets, we have found the hybrid method incapable of correcting the cortical surface appropriately when a handles and holes exist in close proximity. In several cases, holes in the anatomical surface were labeled as handles thus resulting in discontinuities in the folding pattern. The image-based approach in this study was found to correct the topology in all ten cases within a reasonable time. Furthermore, the distance between the original and corrected surfaces, thickness of brain cortex, curvatures and surface areas are provided as assessments of the approach based on our datasets.

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