Automated retina identification based on multiscale elastic registration. (1st December 2016)

• Record Type: Journal Article
• Authors: Figueiredo, Isabel N.; Moura, Susana; Neves, Júlio S.; Pinto, Luís; Kumar, Sunil; Oliveira, Carlos M.; Ramos, João D.
• Is Part Of: Computers in biology and medicine. Volume 79(2016)
• Page Start: 130
• Page End: 143
• Publication Date: 2016-12-01
• Subjects: Biometrics -- Retina identification -- Retinal fundus images -- Elastic image registration -- Vessel network; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2016.09.019
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: In this work we propose a novel method for identifying individuals based on retinal fundus image matching. The method is based on the image registration of retina blood vessels, since it is known that the retina vasculature of an individual is a signature, i.e., a distinctive pattern of the individual. The proposed image registration consists of a multiscale affine registration followed by a multiscale elastic registration. The major advantage of this particular two-step image registration procedure is that it is able to account for both rigid and non-rigid deformations either inherent to the retina tissues or as a result of the imaging process itself. Afterwards a decision identification measure, relying on a suitable normalized function, is defined to decide whether or not the pair of images belongs to the same individual. The method is tested on a data set of 21 721 real pairs generated from a total of 946 retinal fundus images of 339 different individuals, consisting of patients followed in the context of different retinal diseases and also healthy patients. The evaluation of its performance reveals that it achieves a very low false rejection rate (FRR) at zero FAR (the false acceptance rate), equal to 0.084, as well as a low equal error rate (EER), equal to 0.053. Moreover, the tests performed by using only the multiscale affine registration, and discarding the multiscale elastic registration, clearly show the advantage of the proposed approach. The outcome of this study also indicates that the proposed method is reliable and competitive with other existing retinal identification methods, and forecasts its future appropriateness and applicability in real-life applications. Abstract : Highlights: A novel method for identifying individuals based on retinal fundus image matching. A multiscale elastic registration of the vessel networks is applied. The identification relies on a suitable decision measure. Validation on large data sets evidences the reliability of the method.