Group mean differences of voxel and surface objects via nonlinear averaging

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Publication Type pre-print
School or College <blank>
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Creator Gerig, Guido
Other Author Xu, Shun; Styner, Martin; Davis, Brad; Joshi, Sarang
Title Group mean differences of voxel and surface objects via nonlinear averaging
Date 2006-01-01
Description Building of atlases representing average and variability of a population of images or of segmented objects is a key topic in application areas like brain mapping, deformable object segmentation and object classification. Recent developments in image averaging, i.e. constructing an image which is central within the population, focus on unbiased atlas building with nonlinear deformations. Groupwise nonlinear image averaging creates images which appear sharper than linear results. However, volumetric atlases do not explicitely carry a notion of statistics of embedded shapes. This paper compares population-based linear and non-linear image averaging on 3D objects segmented from each image and compares voxel-based versus surface-based representations. Preliminary results suggest improved locality of group average differences for the nonlinear scheme, which might lead to increased significance for hypothesis testing. Results from a clinical MRI study with sets of subcortical structures of children scanned at two years with follow-up at four years are shown.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Issue 758
First Page 761
Language eng
Bibliographic Citation Xu, S., Styner, M., Davis, B., Joshi, S., & Gerig, G. (2006). Group mean differences of voxel and surface objects via nonlinear averaging. Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), 758-61.
Rights Management (c) 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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Date Created 2015-02-17
Date Modified 2021-05-06
ID 712821
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