3D brain mapping using a deformable neuroanatomy.
This paper presents two different mathematical methods that can be used separately or in conjunction to accommodate shape variabilities between normal human neuroanatomies. Both methods use a digitized textbook to represent the complex structure of a typical normal neuroanatomy. Probabilistic transformations on the textbook coordinate system are defined to accommodate shape differences between the textbook and images of other normal neuroanatomies. The transformations are constrained to be consistent with the physical properties of deformable elastic solids in the first method and those of viscous fluids in the second. Results presented in this paper demonstrate how a single deformable textbook can be used to accommodate normal shape variability.
Christensen
G E
GE
The Institute for Biomedical Computing and The Electronic Signals and Systems Research Laboratory, Washington University, St Louis, MO 63130, USA.
Rabbitt
R D
RD
Miller
M I
MI
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D008962:Models, Theoretical; D009474:Neurons / Q000378:metabolism / Q000473:pathology*; D013997:Time Factors