Modeling the brain morphology distribution in the general aging population

W. Huizinga; D. H.J. Poot; G. Roshchupkin; E. E. Bron; M. A. Ikram; M. W. Vernooij; Daniel Rueckert; W. J. Niessen; S. Klein

doi:10.1117/12.2207228

Modeling the brain morphology distribution in the general aging population

W. Huizinga^*
, D. H.J. Poot
, G. Roshchupkin
, E. E. Bron
, M. A. Ikram
, M. W. Vernooij
, Daniel Rueckert
, W. J. Niessen
, S. Klein

^*Corresponding author for this work

Imperial College London
Delft University of Technology

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

3 Citations (Scopus)

Abstract

Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

Original language	English
Title of host publication	Medical Imaging 2016
Subtitle of host publication	Biomedical Applications in Molecular, Structural, and Functional Imaging
Editors	Barjor Gimi, Andrzej Krol
Publisher	SPIE
ISBN (Electronic)	9781510600232
DOIs	https://doi.org/10.1117/12.2207228
Publication status	Published - 2016
Event	Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, United States Duration: 1 Mar 2016 → 3 Mar 2016

Publication series

Series	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	9788
ISSN	1605-7422

Conference

Conference	Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/Territory	United States
City	San Diego
Period	1/03/16 → 3/03/16

Bibliographical note

Publisher Copyright:
© 2016 SPIE.

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10.1117/12.2207228

Cite this

Huizinga, W., Poot, D. H. J., Roshchupkin, G., Bron, E. E., Ikram, M. A., Vernooij, M. W., Rueckert, D., Niessen, W. J., & Klein, S. (2016). Modeling the brain morphology distribution in the general aging population. In B. Gimi, & A. Krol (Eds.), Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging Article 97880I SPIE. https://doi.org/10.1117/12.2207228

@inproceedings{11c79561dad14470a4e8bec92d829a8c,

title = "Modeling the brain morphology distribution in the general aging population",

abstract = "Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.",

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year = "2016",

doi = "10.1117/12.2207228",

language = "English",

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Huizinga, W, Poot, DHJ , Roshchupkin, G , Bron, EE , Ikram, MA , Vernooij, MW, Rueckert, D, Niessen, WJ & Klein, S 2016, Modeling the brain morphology distribution in the general aging population. in B Gimi & A Krol (eds), Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging., 97880I, SPIE, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, San Diego, United States, 1/03/16. https://doi.org/10.1117/12.2207228

Modeling the brain morphology distribution in the general aging population. / Huizinga, W.; Poot, D. H.J.; Roshchupkin, G. et al.
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. ed. / Barjor Gimi; Andrzej Krol. SPIE, 2016. 97880I (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 9788).

Research output: Chapter/Conference proceeding › Conference proceeding › Academic › peer-review

TY - GEN

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AU - Huizinga, W.

AU - Poot, D. H.J.

AU - Roshchupkin, G.

AU - Bron, E. E.

AU - Ikram, M. A.

AU - Vernooij, M. W.

AU - Rueckert, Daniel

AU - Niessen, W. J.

AU - Klein, S.

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N2 - Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

AB - Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

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Huizinga W, Poot DHJ , Roshchupkin G , Bron EE , Ikram MA , Vernooij MW et al. Modeling the brain morphology distribution in the general aging population. In Gimi B, Krol A, editors, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. SPIE. 2016. 97880I. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 9788). doi: 10.1117/12.2207228

Modeling the brain morphology distribution in the general aging population

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