3D Gabor wavelets for evaluating medical image registration algorithms

Linlin Shen, Dorothee Auer, Li Bai

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review


A Gabor wavelets based method is proposed in this paper for evaluating and tuning the parameters of image registration algorithms. The registration quality is measured by the anatomical variability of the registered images. We propose in this paper a local anatomical structure descriptor, namely the Maximum Responded Gabor Wavelet (MRGW) for such a purpose. The effectiveness of the descriptor is demonstrated through a practical spatial normalization example - the variance of MRGW is successfully applied to tune the parameters of a nonlinear spatial normalization algorithm, which is integrated in one of the most popular software packages for medical image processing - the Statistical Parametric Mapping (SPM).

Original languageEnglish
Title of host publicationMedical Imaging and Augmented Reality - Third International Workshop
PublisherSpringer Verlag
Number of pages8
ISBN (Print)3540372202, 9783540372202
Publication statusPublished - 2006
Externally publishedYes
Event3rd International Workshop on Medical Imaging and Augmented Reality - Shanghai, China
Duration: 17 Aug 200618 Aug 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4091 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Workshop on Medical Imaging and Augmented Reality


  • 3D Gabor Wavelets
  • Medical Image Registration

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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