VOLUMETRIC TRANSFORMATION OF BRAIN ANATOMY

This paper presents diffeomorphic transformations of three-dimensional (3-D) anatomical image data of the macaque occipital lobe and whole b rain cryosection imagery and of deep brain structures in human brains as imaged via magnetic resonance imagery, These transformations are ge nerated in a hierarchical manner, accommodating both global and local anatomical detail, The initial low-dimensional registration is accompl ished by constraining the transformation to be in a low-dimensional ba sis, The basis is defined by the Green's function of the elasticity op erator placed at predefined locations in the anatomy and the eigenfunc tions of the elasticity operator, The high-dimensional large deformati ons are vector fields generated via the mismatch between the template and target-image volumes constrained to be the solution of a Navier-St okes fluid model. As part of this procedure, the Jacobian of the trans formation is tracked, insuring the generation of diffeomorphisms. It i s shown that transformations constrained by quadratic regularization m ethods such as the Laplacian, biharmonic, and linear elasticity models , do not ensure that the transformation maintains topology and, theref ore, must only be used for coarse global registration.