Correspondence detection using wavelet-based attribute vectors

Zhong Xue, Dinggang Shen, Christos Davatzikos

Research output: Contribution to journalConference article

4 Scopus citations

Abstract

Finding point correspondence in anatomical images is a key step in shape analysis and deformable registration. This paper proposes an automatic correspondence detection algorithm using wavelet-based attribute vectors defined on every image voxel. The attribute vector reflects the anatomical characteristics in a large neighborhood around the respective voxel. It plays the role of a morphological signature for each voxel and is therefore made as distinctive as possible. Correspondence is then determined via similarity of attribute vectors. Experiments with brain MR images show that the algorithm performs at least as well as human experts, even for complex cortical structures.

Original languageEnglish (US)
Pages (from-to)762-770
Number of pages9
JournalLecture Notes in Computer Science
Volume2879
Issue numberPART 2
DOIs
StatePublished - 2003
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada
Duration: Nov 15 2003Nov 18 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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