Literature DB >> 11707092

Voxel-based morphometry using the RAVENS maps: methods and validation using simulated longitudinal atrophy.

C Davatzikos1, A Genc, D Xu, S M Resnick.   

Abstract

Statistical analysis of anatomical maps in a stereotaxic space has been shown to be a useful tool in population-based studies for quantifying local anatomical differences or changes, without a priori assumptions about the location and extent of the regions of interest. This paper presents an extension and validation of a previously published methodology, referred to as RAVENS, for characterizing regional atrophy in the brain. A new method for elastic, volume-preserving spatial normalization, which allows for accurate quantification of very localized atrophy, is used. The RAVENS methodology was tested on images with simulated atrophy within two gyri: precentral and superior temporal. It was found to accurately determine the regions of atrophy, despite their localized nature and the interindividual variability of cortical structures. Moreover, it was found to perform substantially better than the voxel-based morphology method of SPM'99. Improved sensitivity was achieved at the expense of human effort involved in defining a number of sulcal curves that serve as constraints on the 3D elastic warping. Copyright 2001 Academic Press.

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Year:  2001        PMID: 11707092     DOI: 10.1006/nimg.2001.0937

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  186 in total

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2.  Alcohol consumption and premotor corpus callosum in older adults.

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7.  Use of normative distribution of gray to white matter ratio in orthogonal planes in human brain studies and computer-assisted neuroradiology.

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8.  Structural consequences of diffuse traumatic brain injury: a large deformation tensor-based morphometry study.

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Journal:  Neuroimage       Date:  2007-10-13       Impact factor: 6.556

9.  Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization.

Authors:  Aristeidis Sotiras; Susan M Resnick; Christos Davatzikos
Journal:  Neuroimage       Date:  2014-12-12       Impact factor: 6.556

10.  Supervised block sparse dictionary learning for simultaneous clustering and classification in computational anatomy.

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Journal:  Med Image Comput Comput Assist Interv       Date:  2014
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