Journal article
Subject-Specific Longitudinal Shape Analysis by Coupling Spatiotemporal Shape Modeling with Medial Analysis
Proceedings of SPIE, the international society for optical engineering, Vol.10133, pp.101331A-101331A-7
04/2017
DOI: 10.1117/12.2254675
PMCID: PMC5617643
PMID: 28966430
Abstract
Modeling subject-specific shape change is one of the most important challenges in longitudinal shape analysis of disease progression. Whereas anatomical change over time can be a function of normal aging; anatomy can also be impacted by disease related degeneration. Shape changes to anatomy may also be affected by external structural changes from neighboring structures, which may cause non-linear pose variations. In this paper, we propose a framework to analyze disease related shape changes by coupling extrinsic modeling of the ambient anatomical space via spatiotemporal deformations with intrinsic shape properties from medial surface analysis. We compare intrinsic shape properties of a subject-specific shape trajectory to a normative 4D shape atlas representing normal aging to separately quantify shape changes related to disease. The spatiotemporal shape modeling establishes inter/intra subject anatomical correspondence, which in turn enables comparisons between subjects and the 4D shape atlas, and also quantitative analysis of disease related shape change. The medial surface analysis captures intrinsic shape properties related to local patterns of deformation. The proposed framework simultaneously models extrinsic longitudinal shape changes in the ambient anatomical space, as well as intrinsic shape properties to give localized measurements of degeneration. Six high risk subjects and six controls are randomly sampled from a Huntington's disease image database for quantitative and qualitative comparison.
Details
- Title: Subtitle
- Subject-Specific Longitudinal Shape Analysis by Coupling Spatiotemporal Shape Modeling with Medial Analysis
- Creators
- Sungmin Hong - Computer Science and Engineering, Tandon School of Engineering, New York UniversityJames Fishbaugh - Computer Science and Engineering, Tandon School of Engineering, New York UniversityMorteza Rezanejad - School of Computer Science, McGill UniversityKaleem Siddiqi - School of Computer Science, McGill UniversityHans Johnson - Department of Psychiatry, Carver College of Medicine, University of IowaJane Paulsen - Department of Psychiatry, Carver College of Medicine, University of IowaEun Young Kim - Department of Psychiatry, Carver College of Medicine, University of IowaGuido Gerig - Computer Science and Engineering, Tandon School of Engineering, New York University
- Resource Type
- Journal article
- Publication Details
- Proceedings of SPIE, the international society for optical engineering, Vol.10133, pp.101331A-101331A-7
- DOI
- 10.1117/12.2254675
- PMID
- 28966430
- PMCID
- PMC5617643
- NLM abbreviation
- Proc SPIE Int Soc Opt Eng
- ISSN
- 0277-786X
- eISSN
- 1996-756X
- Grant note
- U54 EB005149 / NIBIB NIH HHS R01 NS040068 / NINDS NIH HHS U01 NS082086 / NINDS NIH HHS R01 NS054893 / NINDS NIH HHS R01 NS050568 / NINDS NIH HHS
- Language
- English
- Date published
- 04/2017
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Psychiatry; Psychological and Brain Sciences; The Iowa Institute for Biomedical Imaging; The Iowa Initiative for Artificial Intelligence; Iowa Informatics Initiative
- Record Identifier
- 9984221629202771
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