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PubMed · 9788072

k-tree method for high-speed spatial normalization.

J L Lancaster·P V Kochunov·P T Fox·D Nickerson
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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 256(3) image arrays is attainable on a Sun Ultra30 workstation.

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AlgorithmsBrain MappingComputer SimulationHumansMagnetic Resonance ImagingStereotaxic TechniquesJournal ArticleResearch Support, U.S. Gov't, P.H.S.

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J L Lancaster, P V Kochunov, P T Fox, D Nickerson. 1998. k-tree method for high-speed spatial normalization.. https://pubmed.ncbi.nlm.nih.gov/9788072/

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