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IEEE Trans Med Imaging. 2007 Apr;26(4):566-81.

Weighted fourier series representation and its application to quantifying the amount of gray matter.

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  • 1Department of Statistics, Biostatistics, and Medical Informatics, and the Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, WI 53706, USA. mchung@stat.wisc.edu

Abstract

We present a novel weighted Fourier series (WFS) representation for cortical surfaces. The WFS representation is a data smoothing technique that provides the explicit smooth functional estimation of unknown cortical boundary as a linear combination of basis functions. The basic properties of the representation are investigated in connection with a self-adjoint partial differential equation and the traditional spherical harmonic (SPHARM) representation. To reduce steep computational requirements, a new iterative residual fitting (IRF) algorithm is developed. Its computational and numerical implementation issues are discussed in detail. The computer codes are also available at http://www.stat.wisc.edu/-mchung/softwares/weighted.SPHARM/weighted-SPHARM.html. As an illustration, the WFS is applied i n quantifying the amount ofgray matter in a group of high functioning autistic subjects. Within the WFS framework, cortical thickness and gray matter density are computed and compared.

PMID:
17427743
DOI:
10.1109/TMI.2007.892519
[PubMed - indexed for MEDLINE]
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