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Proceedings Paper

Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis
Author(s): Alan C. Evans; Weiqian Dai; D. Louis Collins; Peter Neelin; Sean Marrett
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Paper Abstract

We describe the implementation, experience and preliminary results obtained with a 3-D computerized brain atlas for topographical and functional analysis of brain sub-regions. A volume-of-interest (VOI) atlas was produced by manual contouring on 64 adjacent 2 mm-thick MRI slices to yield 60 brain structures in each hemisphere which could be adjusted, originally by global affine transformation or local interactive adjustments, to match individual MRI datasets. We have now added a non-linear deformation (warp) capability (Bookstein, 1989) into the procedure for fitting the atlas to the brain data. Specific target points are identified in both atlas and MRI spaces which define a continuous 3-D warp transformation that maps the atlas on to the individual brain image. The procedure was used to fit MRI brain image volumes from 16 young normal volunteers. Regional volume and positional variability were determined, the latter in such a way as to assess the extent to which previous linear models of brain anatomical variability fail to account for the true variation among normal individuals. Using a linear model for atlas deformation yielded 3-D fits of the MRI data which, when pooled across subjects and brain regions, left a residual mis-match of 6 - 7 mm as compared to the non-linear model. The results indicate a substantial component of morphometric variability is not accounted for by linear scaling. This has profound implications for applications which employ stereotactic coordinate systems which map individual brains into a common reference frame: quantitative neuroradiology, stereotactic neurosurgery and cognitive mapping of normal brain function with PET. In the latter case, the combination of a non-linear deformation algorithm would allow for accurate measurement of individual anatomic variations and the inclusion of such variations in inter-subject averaging methodologies used for cognitive mapping with PET.

Paper Details

Date Published: 1 June 1991
PDF: 11 pages
Proc. SPIE 1445, Medical Imaging V: Image Processing, (1 June 1991); doi: 10.1117/12.45221
Show Author Affiliations
Alan C. Evans, Montreal Neurological Institute/McGill Univ. (Canada)
Weiqian Dai, Montreal Neurological Institute/McGill Univ. (Canada)
D. Louis Collins, Montreal Neurological Institute/McGill Univ. (Canada)
Peter Neelin, Montreal Neurological Institute/McGill Univ. (Canada)
Sean Marrett, Montreal Neurological Institute/McGill Univ. (Canada)


Published in SPIE Proceedings Vol. 1445:
Medical Imaging V: Image Processing
Murray H. Loew, Editor(s)

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