3D BRAIN MAPPING USING A DEFORMABLE NEUROANATOMY

This paper presents two different mathematical methods that can be use d separately or in conjunction to accommodate shape variabilities betw een 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 de fined to accommodate shape differences between the textbook and images of other normal neuroanatomies. The transformations are constrained t o be consistent with the physical properties of deformable elastic sol ids in the first method and those of viscous fluids in the second. Res ults presented in this paper demonstrate how a single deformable textb ook can be used to accommodate normal shape variability.