Anatomical global spatial normalization

Jack L Lancaster, Matthew D. Cykowski, David Reese McKay, Peter V. Kochunov, Peter T Fox, William E Rogers, Arthur W. Toga, Karl Zilles, Katrin Amunts, John Mazziotta

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Anatomical global spatial normalization (aGSN) is presented as a method to scale high-resolution brain images to control for variability in brain size without altering the mean size of other brain structures. Two types of mean preserving scaling methods were investigated, "shape preserving" and "shape standardizing". aGSN was tested by examining 56 brain structures from an adult brain atlas of 40 individuals (LPBA40) before and after normalization, with detailed analyses of cerebral hemispheres, all gyri collectively, cerebellum, brainstem, and left and right caudate, putamen, and hippocampus. Mean sizes of brain structures as measured by volume, distance, and area were preserved and variance reduced for both types of scale factors. An interesting finding was that scale factors derived from each of the ten brain structures were also mean preserving. However, variance was best reduced using whole brain hemispheres as the reference structure, and this reduction was related to its high average correlation with other brain structures. The fractional reduction in variance of structure volumes was directly related to ρ 2, the square of the reference-to-structure correlation coefficient. The average reduction in variance in volumes by aGSN with whole brain hemispheres as the reference structure was approximately 32%. An analytical method was provided to directly convert between conventional and aGSN scale factors to support adaptation of aGSN to popular spatial normalization software packages.

Original languageEnglish (US)
Pages (from-to)171-182
Number of pages12
JournalNeuroinformatics
Volume8
Issue number3
DOIs
StatePublished - Oct 2010

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Brain
Atlases
Putamen
Cerebrum
Software packages
Cerebellum
Brain Stem
Hippocampus
Software

Keywords

  • AGSN
  • Area
  • GSN
  • Linear distance
  • Mean volume
  • Size preservation
  • Variance

ASJC Scopus subject areas

  • Neuroscience(all)
  • Information Systems
  • Software

Cite this

Lancaster, J. L., Cykowski, M. D., McKay, D. R., Kochunov, P. V., Fox, P. T., Rogers, W. E., ... Mazziotta, J. (2010). Anatomical global spatial normalization. Neuroinformatics, 8(3), 171-182. https://doi.org/10.1007/s12021-010-9074-x

Anatomical global spatial normalization. / Lancaster, Jack L; Cykowski, Matthew D.; McKay, David Reese; Kochunov, Peter V.; Fox, Peter T; Rogers, William E; Toga, Arthur W.; Zilles, Karl; Amunts, Katrin; Mazziotta, John.

In: Neuroinformatics, Vol. 8, No. 3, 10.2010, p. 171-182.

Research output: Contribution to journalArticle

Lancaster, JL, Cykowski, MD, McKay, DR, Kochunov, PV, Fox, PT, Rogers, WE, Toga, AW, Zilles, K, Amunts, K & Mazziotta, J 2010, 'Anatomical global spatial normalization', Neuroinformatics, vol. 8, no. 3, pp. 171-182. https://doi.org/10.1007/s12021-010-9074-x
Lancaster JL, Cykowski MD, McKay DR, Kochunov PV, Fox PT, Rogers WE et al. Anatomical global spatial normalization. Neuroinformatics. 2010 Oct;8(3):171-182. https://doi.org/10.1007/s12021-010-9074-x
Lancaster, Jack L ; Cykowski, Matthew D. ; McKay, David Reese ; Kochunov, Peter V. ; Fox, Peter T ; Rogers, William E ; Toga, Arthur W. ; Zilles, Karl ; Amunts, Katrin ; Mazziotta, John. / Anatomical global spatial normalization. In: Neuroinformatics. 2010 ; Vol. 8, No. 3. pp. 171-182.
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