Unbiased diffeomorphic atlas construction for computational anatomy

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Publication Type pre-print
School or College <blank>
Department <blank>
Creator Gerig, Guido
Other Author Joshi, S.; Davis, Brad; Jomier, Matthieu
Title Unbiased diffeomorphic atlas construction for computational anatomy
Date 2004-01-01
Description Construction of population atlases is a key issue in medical image analysis, and particularly in brain mapping. Large sets of images are mapped into a common coordinate system to study intra-population variability and inter-population differences, to provide voxel-wise mapping of functional sites, and help tissue and object segmentation via registration of anatomical labels. Common techniques often include the choice of a template image, which inherently introduces a bias. This paper describes a new method for unbiased construction of atlases in the large deformation diffeomorphic setting. A child neuroimaging autism study serves as a driving application. There is lack of normative data that explains average brain shape and variability at this early stage of development. We present work in progress toward constructing an unbiased MRI atlas of two year of children and the building of a probabilistic atlas of anatomical structures, here the caudate nucleus. Further, we demonstrate the segmentation of new subjects via atlas mapping. Validation of the methodology is performed by comparing the deformed probabilistic atlas with existing manual segmentations.
Type Text
Publisher Elsevier
Volume 23
Issue suppl.1
First Page S151
Last Page S160
Language eng
Bibliographic Citation Joshi, S., Davis, B., Jomier, M., & Gerig, G. (2004). Unbiased diffeomorphic atlas construction for computational anatomy. Neuroimage, 23(suppl. 1), S151-S60.
Rights Management (c) Elsevier ; Authors manuscript from Joshi, S., Davis, B., Jomier, M., & Gerig, G. (2004). Unbiased diffeomorphic atlas construction for computational anatomy. Neuroimage, 23(suppl. 1), S151-S60. http://dx.doi.org/10.1016/j.neuroimage.2004.07.068.
Format Medium application/pdf
Format Extent 2,395,954 bytes
Identifier uspace,19295
ARK ark:/87278/s6fr35r6
Setname ir_uspace
ID 712878
Reference URL https://collections.lib.utah.edu/ark:/87278/s6fr35r6
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