Paul Thompson's Research Publications
Evaluation of Octree Regional Spatial Normalization (OSN) Method for Regional Anatomical Matching
Human Brain Mapping 11:193-206, November 2000
Peter Kochunov 1, Jack Lancaster 1, Paul M. Thompson 2,
A. Boyer 3, J. Hardies 1, Peter T. Fox 1
1Research Imaging Center, University of Texas Health Science Center at San
Antonio, San Antonio, Texas
2Laboratory of Neuro Imaging, Department of
Neurology, Division of
Brain Mapping, UCLA School of Medicine, Los Angeles, California
90095
3Department of Radiation Oncology, Stanford University, Stanford, California
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ABSTRACT
The goal of regional spatial normalization is to remove anatomical differences
between individual three-dimensional (3D) brain images by warping them to match
features of a standard brain atlas. Processing to fit features at the limiting
resolution of a 3D MR image volume is computationally intensive, limiting the
broad use of full-resolution regional spatial normalization. In Kochunov et al.
(1999: NeuroImage 10:724-737), we proposed a regional spatial normalization
algorithm called octree spatial normalization (OSN) that reduces processing time
to minutes while targeting the accuracy of previous methods. In the current study,
modifications of the OSN algorithm for use in human brain images are described and
tested. An automated brain tissue segmentation procedure was adopted to create
anatomical templates to drive feature matching in white matter, gray matter, and
cerebral-spinal fluid. Three similarity measurement functions (fast-cross
correlation (CC), sum-square error, and centroid) were evaluated in a group of six
subjects. A combination of fast-CC and centroid was found to provide the best
feature matching and speed. Multiple iterations and multiple applications of the
OSN algorithm were evaluated to improve fit quality. Two applications of the OSN
algorithm with two iterations per application were found to significantly reduce
volumetric mismatch (up to six times for lateral ventricle) while keeping
processing time under 30 min. The refined version of OSN was tested with
anatomical landmarks from several major sulci in a group of nine subjects.
Anatomical variability was appreciably reduced for every sulcus investigated, and
mean sulcal tracings accurately followed sulcal tracings in the target brain.
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Related Publications
A Population-Based Brain Atlas
AN ALZHEIMER'S DISEASE BRAIN ATLAS
Disease-Specific Brain Atlases
other research areas
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Contact Information
Mail:
Paul Thompson, Ph.D.
Assistant Professor of Neurology
Laboratory of Neuro Imaging and Division of Brain Mapping
710 Westwood Plaza, UCLA School of Medicine
Westwood, Los Angeles CA 90095-1761, USA.
E-mail:
thompson@loni.ucla.edu
Tel: (310)206-2101
Fax: (310)206-5518