Abstract
The general approach to spatial normalization using a deformation field is presented. Current high degree-of-freedom deformation methods are extremely time-consuming (10–40 hr), and a k-tree method is proposed to greatly reduce this time. A general k-tree method for analysis of source and target images and synthesis of deformation fields is described. The k-tree method simplifies scale control and feature extraction and matching, making it highly efficient. A two-dimensional (2-D), or quadtree, application program was developed for preliminary testing. The k-tree method was evaluated with 2-D images to test rotating ability, nonhomologous region matching, inner and outer brain-structure independence, and feasibility with human brain images. The results of these tests indicate that a three-dimensional (3-D), or octree, method is feasible. Preliminary work with an octree application program indicates that a processing time of under 10 min for 2563 image arrays is attainable on a Sun Ultra30 workstation. Hum. Brain Mapping 6:358–363, 1998. © 1998 Wiley-Liss, Inc.
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