A robust model for the automatic segmentation of human brain images into anatomically defined regions across the
human lifespan would be highly desirable, but such structural segmentations of brain MRI are challenging due to age-related
changes. We have developed a new method, based on established algorithms for automatic segmentation of
young adults' brains. We used prior information from 30 anatomical atlases, which had been manually segmented into
83 anatomical structures. Target MRIs came from 80 subjects (~12 individuals/decade) from 20 to 90 years, with equal
numbers of men, women; data from two different scanners (1.5T, 3T), using the IXI database. Each of the adult atlases
was registered to each target MR image. By using additional information from segmentation into tissue classes (GM,
WM and CSF) to initialise the warping based on label consistency similarity before feeding this into the previous
normalised mutual information non-rigid registration, the registration became robust enough to accommodate atrophy
and ventricular enlargement with age. The final segmentation was obtained by combination of the 30 propagated atlases
using decision fusion. Kernel smoothing was used for modelling the structural volume changes with aging. Example
linear correlation coefficients with age were, for lateral ventricular volume, rmale=0.76, rfemale=0.58 and, for hippocampal
volume, rmale=-0.6, rfemale=-0.4 (allρ<0.01).
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.