k-Tree method for high-speed spatial normalization

Jack L. Lancaster, Peter V. Kochunov, Peter T. Fox, Daniel Nickerson

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


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 languageEnglish (US)
Pages (from-to)358-363
Number of pages6
JournalHuman Brain Mapping
Issue number5-6
StatePublished - 1998
Externally publishedYes


  • Octree
  • Quadtree
  • Spatial normalization
  • k-Tree

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology


Dive into the research topics of 'k-Tree method for high-speed spatial normalization'. Together they form a unique fingerprint.

Cite this