QUT ePrints

Quadrature-based image registration method using Mutual Information

Fookes, Clinton B. & Maeder, Anthony J. (2004) Quadrature-based image registration method using Mutual Information. In IEEE International Symposium on Biomedical Imaging : From Nano to Macro, April 15-18, 2004, Arlington, Virginia.

View at publisher

Abstract

Mutual information (MI) is a popular entropy-based similarity measure used in the medical imaging field for multimodal 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-basedMI techniques. These results are achieved using half the previously required sample sizes and also with an improvement in algorithm complexity.

Impact and interest:

5 citations in Scopus
Search Google Scholar™
0 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

134 since deposited on 16 Feb 2009
3 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 17912
Item Type: Conference Paper
Additional URLs:
Keywords: Image Registration, Mutual Information, Quadrature
DOI: 10.1109/ISBI.2004.1398641
ISBN: 0780383885
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2004 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 16 Feb 2009 14:33
Last Modified: 09 Jun 2010 23:23

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page