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.
Original language | English (US) |
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Pages (from-to) | 358-363 |
Number of pages | 6 |
Journal | Human Brain Mapping |
Volume | 6 |
Issue number | 5-6 |
DOIs | |
State | Published - 1998 |
Keywords
- Octree
- Quadtree
- Spatial normalization
- k-Tree
ASJC Scopus subject areas
- Anatomy
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Neurology
- Clinical Neurology