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Feature neighbourhood mutual information for multi-modal image registration: An application to eye fundus imaging

Rosin, Paul L. ORCID: 2015. Feature neighbourhood mutual information for multi-modal image registration: An application to eye fundus imaging. Pattern Recognition 48 (6) , pp. 1937-1946. 10.1016/j.patcog.2014.12.014

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Multi-modal image registration is becoming an increasingly powerful tool for medical diagnosis and treatment. The combination of different image modalities facilitates much greater understanding of the underlying condition, resulting in improved patient care. Mutual Information is a popular image similarity measure for performing multi-modal image registration. However, it is recognised that there are limitations with the technique that can compromise the accuracy of the registration, such as the lack of spatial information that is accounted for by the similarity measure. In this paper, we present a two-stage non-rigid registration process using a novel similarity measure, Feature Neighbourhood Mutual Information. The similarity measure efficiently incorporates both spatial and structural image properties that are not traditionally considered by MI. By incorporating such features, we find that this method is capable of achieving much greater registration accuracy when compared to existing methods, whilst also achieving efficient computational runtime. To demonstrate our method, we use a challenging medical image data set consisting of paired retinal fundus photographs and confocal scanning laser ophthalmoscope images. Accurate registration of these image pairs facilitates improved clinical diagnosis, and can be used for the early detection and prevention of glaucoma disease.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RE Ophthalmology
Uncontrolled Keywords: Mutual information; Feature derivatives; Gauge co-ordinates; Non-rigid registration; Ophthalmology
Publisher: Elsevier
Date of Acceptance: 17 December 2014
Last Modified: 31 Oct 2022 04:41

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