Statistics of populations of images and its embedded objects: driving applications in neuroimaging

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Publication Type journal article
School or College <blank>
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Creator Gerig, Guido
Other Author Joshi, S.; Fletcher, P. T.; Gorczowski, K.; Xu, S.; Pizer, S. M.; Styner, M.
Title Statistics of populations of images and its embedded objects: driving applications in neuroimaging
Date 2006-01-01
Description Work in progress towards modeling shape statistics of multi-object complexes is presented. Constraints defined by the set of objects such as a compact representation of object shape relationships and correlation of shape changes might have advantages for automatic segmentation and group discrimination. We present a concept for statistical multi-object modeling and discuss the major challenges which are a reduction to a small set of descriptive features, calculation of mean and variability via curved statistics, the choice of aligning sets of multiple objects, and the problem of describing the statistics of object pose and object shape and their interrelationship. Shape modeling and analysis is demonstrated with an application to a longitudinal autism study, with shape modeling of sets of 10 subcortical structures in a population of 20 subjects.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 1120
Last Page 1123
Language eng
Bibliographic Citation Gerig, G., Joshi, S., Fletcher, P. T., Gorczowski, K., Xu, S., Pizer, S. M., & Styner, M. (2006). Statistics of populations of images and its embedded objects: driving applications in neuroimaging. Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI), 1120-3.
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.
Format Medium application/pdf
Format Extent 369,600 bytes
Identifier uspace,19271
ARK ark:/87278/s6gx7mp7
Setname ir_uspace
Date Created 2015-02-09
Date Modified 2015-02-09
ID 712808
Reference URL https://collections.lib.utah.edu/ark:/87278/s6gx7mp7
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