Attribute vector guided groupwise registration

Qian Wang, Pew Thian Yap, Guorong Wu, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Groupwise registration has been recently introduced for simultaneous registration of a group of images with the goal of constructing an unbiased atlas. To this end, direct application of information-theoretic entropy measures on image intensity has achieved various successes. However, simplistic voxelwise utilization of image intensity often neglects important contextual information, which can be provided by more comprehensive geometric and statistical features. In this paper, we employ attribute vectors, instead of image intensities, to guide groupwise registration. In particular, for each voxel, the attribute vector is computed from its multiple-scale neighborhoods to capture geometric information at different scales. Moreover, the probability density function (PDF) of each attribute in the vector is then estimated from the local neighborhood, providing a statistical summary of the underlying anatomical structure. For the purpose of registration, Jensen-Shannon (JS) divergence is used to measure the PDF dissimilarity of each attribute at corresponding locations of different individual images. By minimizing the overall JS divergence in the whole image space and estimating the deformation field of each image simultaneously, we can eventually register all images and build an unbiased atlas. Experimental results indicate that our method yields better registration quality, compared with a popular groupwise registration method.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages656-663
Number of pages8
Volume5761 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2009 Dec 1
Externally publishedYes
Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
Duration: 2009 Sep 202009 Sep 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5761 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
CountryUnited Kingdom
CityLondon
Period09/9/2009/9/24

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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