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A Feature-based Developmental Model of the Infant Brain in Structural MRI

Institution:
1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. mt@bwh.harvard.edu
2Massachussetts General Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
Int Conf Med Image Comput Comput Assist Interv. MICCAI 2012
Publication Date:
Oct-2012
Journal:
Med Image Comput Comput Assist Interv
Volume Number:
15
Issue Number:
Pt 2
Pages:
204-11
Citation:
Int Conf Med Image Comput Comput Assist Interv. 2012 Oct;15(Pt 2):204-11.
PubMed ID:
23286050
PMCID:
PMC4009075
Appears in Collections:
NAC, NA-MIC, SPL
Sponsors:
N01 HD023343/HD/NICHD NIH HHS/United States
N01 MH090002/MH/NIMH NIH HHS/United States
N01 NS092314/NS/NINDS NIH HHS/United States
N01 NS092315/NS/NINDS NIH HHS/United States
N01 NS092316/NS/NINDS NIH HHS/United States
N01 NS092317/NS/NINDS NIH HHS/United States
N01 NS092319/NS/NINDS NIH HHS/United States
N01 NS092320/NS/NINDS NIH HHS/United States
P41 EB015902/EB/NIBIB NIH HHS/United States
P41 RR013218/RR/NCRR NIH HHS/United States
R01 HD057963/HD/NICHD NIH HHS/United States
Generated Citation:
Toews M., Wells III W.M., Zöllei L. A Feature-based Developmental Model of the Infant Brain in Structural MRI. Int Conf Med Image Comput Comput Assist Interv. 2012 Oct;15(Pt 2):204-11. PMID: 23286050. PMCID: PMC4009075.
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In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days.

Additional Material
1 File (235.427kB)
Toews-MICCAI2012-fig1.jpg (235.427kB)