Multi-modal image registration by quantitative-qualitative measure of mutual information (Q-MI)

Hongxia Luan, Feihu Qi, Dinggang Shen

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

9 Citations (Scopus)

Abstract

This paper presents a novel measure of image similarity, called quantitative-qualitative measure of mutual information (Q-MI), for multi-modal image registration. Conventional information measure, i.e., Shannon's entropy, is a quantitative measure of information, since it only considers probabilities, not utilities of events. Actually, each event has its own utility to the fulfillment of the underlying goal, which can be independent of its probability of occurrence. Therefore, it is important to consider both quantitative and qualitative (i.e., utility) information simultaneously for image registration. To achieve this, salient voxels such as white matter (WM) voxels near to brain cortex will be assigned higher utilities than the WM voxels inside the large WM regions, according to the regional saliency values calculated from scale-space map of brain image. Thus, voxels with higher utilities will contribute more in measuring the mutual information of two images under registration. We use this novel measure of mutual information (Q-MI) for registration of multi-modality brain images, and find that the successful rate of our registration method is much higher than that of conventional mutual information registration method.

Original languageEnglish
Title of host publicationComputer Vision for Biomedical Image Applications - First International Workshop, CVBIA 2005, Proceedings
Pages378-387
Number of pages10
DOIs
Publication statusPublished - 2005
Event1st International Workshop on Computer Vision for Biomedical Image Applications, CVBIA 2005 - Beijing, China
Duration: 2005 Oct 212005 Oct 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3765 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Computer Vision for Biomedical Image Applications, CVBIA 2005
CountryChina
CityBeijing
Period05/10/2105/10/21

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Luan, H., Qi, F., & Shen, D. (2005). Multi-modal image registration by quantitative-qualitative measure of mutual information (Q-MI). In Computer Vision for Biomedical Image Applications - First International Workshop, CVBIA 2005, Proceedings (pp. 378-387). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3765 LNCS). https://doi.org/10.1007/11569541_38