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@ARTICLE{Lancaster:10475,
      author       = {Lancaster, J.L. and Cykowski, M.D. and McKay, D.R. and
                      Kochunov, P.V. and Fox, P.T. and Rogers, W. and Toga, A.W.
                      and Zilles, K. and Amunts, K. and Mazziotta, J.},
      title        = {{A}natomical {G}lobal {S}patial {N}ormalization},
      journal      = {Neuroinformatics},
      volume       = {8},
      issn         = {1539-2791},
      address      = {New York, NY},
      publisher    = {Springer},
      reportid     = {PreJuSER-10475},
      pages        = {171 - 182},
      year         = {2010},
      note         = {Research supported by grants from the Human Brain Mapping
                      Project jointly funded by NIMH and NIDA (P20 MH/DA52176),
                      the General Clinical Research Core (HSC19940074H), and NIBIB
                      (K01 EB006395). Additional support was provided through the
                      NIH/National Center for Research Resources through grants
                      P41 RR013642 and U54 RR021813 (Center for Computational
                      Biology (CCB)). Also, support for Cykowski was from
                      F32-DC009116 to MDC (NIH/NIDCD). This work was partly
                      supported by the Initiative and Networking Fund of the
                      Helmholtz Association within the Helmholtz Alliance on
                      Systems Biology (KZ). KA was partly supported by the
                      Bundesministerium fur Bildung und Forschung (01 GW0613,
                      01GW0771, 01GW0623), and the Deutsche Forschungsgemeinschaft
                      (AM 118/1-2).},
      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.},
      keywords     = {Adult / Algorithms / Brain: anatomy $\&$ histology / Brain:
                      physiology / Brain Mapping: methods / Cerebellum: anatomy
                      $\&$ histology / Cerebellum: physiology / Cerebral Cortex:
                      anatomy $\&$ histology / Cerebral Cortex: physiology /
                      Computer Simulation: standards / Female / Humans / Image
                      Processing, Computer-Assisted: methods / Magnetic Resonance
                      Imaging: methods / Male / Models, Statistical / Organ Size:
                      physiology / Young Adult / J (WoSType)},
      cin          = {INM-1 / INM-2 / JARA-BRAIN},
      ddc          = {540},
      cid          = {I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)INM-2-20090406 /
                      $I:(DE-82)080010_20140620$},
      pnm          = {Funktion und Dysfunktion des Nervensystems (FUEK409) /
                      BMBF-01GW0613 - Phänomenologie und Neurobiologie seiner
                      Störungen beim hochfunktionalen Autismus (HFA)
                      (BMBF-01GW0613) / BMBF-01GW0771 - Neuroanatomische
                      Kartierung des frontalen Operculums (BMBF-01GW0771) /
                      BMBF-01GW0623 - Anatomische Basis von Prosodie und Gesang
                      (BMBF-01GW0623) / 89574 - Theory, modelling and simulation
                      (POF2-89574)},
      pid          = {G:(DE-Juel1)FUEK409 / G:(DE-Juel1)BMBF-01GW0613 /
                      G:(DE-Juel1)BMBF-01GW0771 / G:(DE-Juel1)BMBF-01GW0623 /
                      G:(DE-HGF)POF2-89574},
      shelfmark    = {Computer Science, Interdisciplinary Applications /
                      Neurosciences},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:20582489},
      pmc          = {pmc:PMC2945458},
      UT           = {WOS:000282212500004},
      doi          = {10.1007/s12021-010-9074-x},
      url          = {https://juser.fz-juelich.de/record/10475},
}