Model selection for spatiotemporal modeling of early childhood sub-cortical development

James Fishbaugh; Beatriz Paniagua; Mahmoud Mostapha; Martin Styner; Veronica Murphy; John Gilmore; Guido Gerig

doi:10.1117/12.2513030

Model selection for spatiotemporal modeling of early childhood sub-cortical development

James Fishbaugh, Beatriz Paniagua, Mahmoud Mostapha, Martin Styner, Veronica Murphy, John Gilmore, Guido Gerig

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Spatiotemporal shape models capture the dynamics of shape change over time and are an essential tool for monitoring and measuring anatomical growth or degeneration. In this paper we evaluate non-parametric shape regression on the challenging problem of modeling early childhood sub-cortical development starting from birth. Due to the flexibility of the model, it can be challenging to choose parameters which lead to a good model fit yet does not overfit. We systematically test a variety of parameter settings to evaluate model fit as well as the sensitivity of the method to specific parameters, and we explore the impact of missing data on model estimation.

Original language	English (US)
Title of host publication	Medical Imaging 2019
Subtitle of host publication	Image Processing
Editors	Elsa D. Angelini, Elsa D. Angelini, Elsa D. Angelini, Bennett A. Landman
Publisher	SPIE
ISBN (Electronic)	9781510625457
DOIs	https://doi.org/10.1117/12.2513030
State	Published - 2019
Event	Medical Imaging 2019: Image Processing - San Diego, United States Duration: Feb 19 2019 → Feb 21 2019

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	10949
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2019: Image Processing
Country/Territory	United States
City	San Diego
Period	2/19/19 → 2/21/19

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Biomaterials
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.2513030

Cite this

Fishbaugh, J., Paniagua, B., Mostapha, M., Styner, M., Murphy, V., Gilmore, J., & Gerig, G. (2019). Model selection for spatiotemporal modeling of early childhood sub-cortical development. In E. D. Angelini, E. D. Angelini, E. D. Angelini, & B. A. Landman (Eds.), Medical Imaging 2019: Image Processing [109490L] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10949). SPIE. https://doi.org/10.1117/12.2513030

Model selection for spatiotemporal modeling of early childhood sub-cortical development. / Fishbaugh, James; Paniagua, Beatriz; Mostapha, Mahmoud et al.

Medical Imaging 2019: Image Processing. ed. / Elsa D. Angelini; Elsa D. Angelini; Elsa D. Angelini; Bennett A. Landman. SPIE, 2019. 109490L (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 10949).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Fishbaugh, J, Paniagua, B, Mostapha, M, Styner, M, Murphy, V, Gilmore, J & Gerig, G 2019, Model selection for spatiotemporal modeling of early childhood sub-cortical development. in ED Angelini, ED Angelini, ED Angelini & BA Landman (eds), Medical Imaging 2019: Image Processing., 109490L, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10949, SPIE, Medical Imaging 2019: Image Processing, San Diego, United States, 2/19/19. https://doi.org/10.1117/12.2513030

Fishbaugh J, Paniagua B, Mostapha M, Styner M, Murphy V, Gilmore J et al. Model selection for spatiotemporal modeling of early childhood sub-cortical development. In Angelini ED, Angelini ED, Angelini ED, Landman BA, editors, Medical Imaging 2019: Image Processing. SPIE. 2019. 109490L. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.2513030

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abstract = "Spatiotemporal shape models capture the dynamics of shape change over time and are an essential tool for monitoring and measuring anatomical growth or degeneration. In this paper we evaluate non-parametric shape regression on the challenging problem of modeling early childhood sub-cortical development starting from birth. Due to the flexibility of the model, it can be challenging to choose parameters which lead to a good model fit yet does not overfit. We systematically test a variety of parameter settings to evaluate model fit as well as the sensitivity of the method to specific parameters, and we explore the impact of missing data on model estimation.",

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Model selection for spatiotemporal modeling of early childhood sub-cortical development

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