k-tree method for high-speed spatial normalization

✍ Scribed by Jack L. Lancaster; Peter V. Kochunov; Peter T. Fox; Daniel Nickerson

• Publisher: John Wiley and Sons
• Year: 1998
• Tongue: English
• Weight: 145 KB
• Volume: 6
• Category: Article
• ISSN: 1065-9471
• DOI: 10.1002/(sici)1097-0193(1998)6:5/6<358::aid-hbm5>3.0.co;2-l

✦ Synopsis

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.