Quadrature-based image registration method using mutual information

C. Fookes, A. Maeder

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

5 Citations (Scopus)

Abstract

Mutual information (MI) is a popular entropy-based similarity measure used in the medical imaging field for multi-modal registration. The basic concept behind any approach using MI is to find a transformation, which when applied to an image, will maximize the MI between two images. A common implementation of MI involves the use of Parzen windows. This process generally requires two samples of image intensities: one to estimate the underlying intensity distributions and the second to estimate the entropy. This paper presents a novel gradient-based registration algorithm (MIGH) which uses Gauss-Hermite quadrature to estimate the image entropies. The use of this technique provides an effective and efficient way of estimating entropy while bypassing the need to draw a second sample of image intensities. With this technique, it is possible to achieve similar results and registration accuracy when compared to current Parzen-based MI techniques. These results are achieved using half the previously required sample sizes and also with an improvement in algorithm complexity.

Original languageEnglish
Title of host publication2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationMacro to Nano
Pages728-731
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2004
Externally publishedYes
Event2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States
Duration: 15 Apr 200418 Apr 2004

Publication series

Name2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume1

Conference

Conference2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
CountryUnited States
CityArlington, VA
Period15/04/0418/04/04

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  • Cite this

    Fookes, C., & Maeder, A. (2004). Quadrature-based image registration method using mutual information. In 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (pp. 728-731). (2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano; Vol. 1). https://doi.org/10.1109/ISBI.2004.1398641