Analysis of longitudinal shape variability via subject specific growth modeling

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Publication Type pre-print
School or College <blank>
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Creator Gerig, Guido
Other Author Fishbaugh, James; Prastawa, Marcel; Durrleman, Stanley; Piven, Joseph
Title Analysis of longitudinal shape variability via subject specific growth modeling
Date 2012-01-01
Description Statistical analysis of longitudinal imaging data is crucial for understanding normal anatomical development as well as disease progression. This fundamental task is challenging due to the difficulty in modeling longitudinal changes, such as growth, and comparing changes across different populations. We propose a new approach for analyzing shape variability over time, and for quantifying spatiotemporal population differences. Our approach estimates 4D anatomical growth models for a reference population (an average model) and for individuals in different groups. We define a reference 4D space for our analysis as the average population model and measure shape variability through diffeomorphisms that map the reference to the individuals. Conducting our analysis on this 4D space enables straightforward statistical analysis of deformations as they are parameterized by momenta vectors that are located at homologous locations in space and time. We evaluate our method on a synthetic shape database and clinical data from a study that seeks to quantify brain growth differences in infants at risk for autism.
Type Text
Publisher Springer
Volume 7510
First Page 731
Last Page 738
Language eng
Bibliographic Citation Fishbaugh, J., Prastawa, M., Durrleman, S., Piven, J. & Gerig, G. (2012). Analysis of longitudinal shape variability via subject specific growth modeling. Medical Image Computing and Computer-Assisted Intervention - Proceedings of MICCAI 2012, Lecture Notes in Computer Science (LNCS) 7510, 731-8.
Rights Management (c) Springer (The original publication is available at The final publication is available at Springer via 10.1007/978-3-642-33415-3_90.
Format Medium application/pdf
Format Extent 1,333,736 bytes
Identifier uspace,19166
ARK ark:/87278/s6d256r5
Setname ir_uspace
Date Created 2015-02-20
Date Modified 2021-05-06
ID 712832
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