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Tuning and comparing spatial normalization methods

Spatial normalization is a key process in cross-sectional studies of brain structure and function using MRI, fMRI, PET and other imaging techniques. A wide range of 2D surface and 3D image deformation algorithms have been developed, all of which involve design choices that are subject to debate. Mor...

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Published in:	Medical image analysis 2004-09, Vol.8 (3), p.311-323
Main Authors:	Robbins, Steven, Evans, Alan C., Collins, D.Louis, Whitesides, Sue
Format:	Article
Language:	English
Subjects:	Algorithms Anatomical variability measure Brain - anatomy & histology Brain mapping Brain Mapping - methods Humans Image Processing, Computer-Assisted - methods Image registration Imaging, Three-Dimensional Magnetic Resonance Imaging Registration performance measure Surface registration
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container_title	Medical image analysis
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creator	Robbins, Steven Evans, Alan C. Collins, D.Louis Whitesides, Sue
description	Spatial normalization is a key process in cross-sectional studies of brain structure and function using MRI, fMRI, PET and other imaging techniques. A wide range of 2D surface and 3D image deformation algorithms have been developed, all of which involve design choices that are subject to debate. Moreover, most have numerical parameters whose value must be specified by the user. This paper proposes a principled method for evaluating design choices and choosing parameter values. This method can also be used to compare competing spatial normalization algorithms. We demonstrate the method through a performance analysis of a nonaffine registration algorithm for 3D images and a registration algorithm for 2D cortical surfaces.
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subjects	Algorithms Anatomical variability measure Brain - anatomy & histology Brain mapping Brain Mapping - methods Humans Image Processing, Computer-Assisted - methods Image registration Imaging, Three-Dimensional Magnetic Resonance Imaging Registration performance measure Surface registration
title	Tuning and comparing spatial normalization methods
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