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


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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    Contact Information

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    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.

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