Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Incorporating neighbourhood feature derivatives with Mutual Information to improve accuracy of multi-modal image registration

Legg, Philip Alexander, Rosin, Paul L. ORCID:, Marshall, Andrew David ORCID: and Morgan, James Edwards ORCID: 2008. Incorporating neighbourhood feature derivatives with Mutual Information to improve accuracy of multi-modal image registration. Presented at: 12th Annual Conference on Medical Image Understanding and Analysis, Dundee, UK, 2-3 July 2008. Published in: McKenna, Stephen and Hoey, Jesse eds. Medical Image Understanding and Analysis 2008: Proceedings of the 12th Annual Conference University of Dundee, 2-3 July 2008. Dundee: British Machine Vision Association, pp. 39-43.

Full text not available from this repository.


In this paper we present an improved method for performing image registration of different modalities. Russakoff [1] proposed the method of Regional Mutual Information (RMI) which allows neighbourhood information to be considered in the Mutual Information (MI) algorithm. We extend this method by taking local multi-scale feature derivatives in a gauge coordinate frame to represent the structural information of the images [2]. By incorporating these images into RMI, we can combine aspects of both structural and neighbourhood information together, which provides a high level of registration accuracy that is essential in application to the medical domain. Our images to be registered are retinal fundus photographs and SLO (Scanning Laser Ophthalmoscopy) images. The combination of these two modalities has received little attention in image registration, yet could provide much useful information to an Ophthalmic clinician. One application is the detection of glaucoma in its early stages, where prevention of further infection is possible before irreversible damage occurs. Results indicate that our method offers a vast improvement to Regional MI, with 25 of our 26 test images being registered to a high standard.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Optometry and Vision Sciences
Systems Immunity Research Institute (SIURI)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RE Ophthalmology
Additional Information: Conference held 2nd-3rd July 2008, University of Dundee, Dundee, Scotland
Publisher: British Machine Vision Association
ISBN: 1901725359
Related URLs:
Last Modified: 19 Oct 2022 09:51

Citation Data

Actions (repository staff only)

Edit Item Edit Item