A New Smartphone-Based Optic Nerve Head Biometric for Verification and Change Detection
| Autor: | Andrew Combes, David J. Keegan, Jason E. Coleman, Kate Coleman, Fatima Hamroush, Patrick Murtagh, Hector Franco-Penya, Patricia Fitzpatrick, Mary Aiken |
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| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Biometry optic nerve head (ONH) genetic structures Biometrics Computer science Optic Disk deep neural networks (DNNs) Biomedical Engineering Optic disk Glaucoma 03 medical and health sciences 0302 clinical medicine biometric medicine Humans Computer vision New Developments in Vision Research business.industry artificial intelligence medicine.disease eye diseases Ophthalmology 030104 developmental biology Mobile phone Feature (computer vision) 030221 ophthalmology & optometry Optic nerve Neural Networks Computer Smartphone sense organs Artificial intelligence business Host (network) Change detection |
| Zdroj: | Translational Vision Science & Technology |
| ISSN: | 2164-2591 |
| DOI: | 10.1167/tvst.10.8.1 |
| Popis: | Purpose: Lens adapted smartphones are being used regularly instead of ophthalmoscopes. The most common causes of preventable blindness in the world, which are glaucoma and diabetic retinopathy, can develop asymptomatic changes to the optic nerve head (ONH) especially in the developing world where there is a dire shortage of ophthalmologists but ubiquitous mobile phones. We developed a proof-of-concept ONH biometric (application [APP]) to use as a routine biometric on a mobile phone. The unique blood vessel pattern is verified if it maps on to a previously enrolled image. Methods: The iKey APP platform comprises three deep neural networks (DNNs) developed from anonymous ONH images: the graticule blood vessel (GBV) and the blood vessel specific feature (BVSF) DNNs were trained on unique blood vessel vectors. A non-feature specific (NFS) baseline ResNet50 DNN was trained for comparison. Results: Verification reached an accuracy of 97.06% with BVSF, 87.24% with GBV and 79.8% using NFS. Conclusions: A new ONH biometric was developed with a hybrid platform of ONH algorithms for use as a verification biometric on a smartphone. Failure to verify will alert the user to possible changes to the image, so that silent changes may be observed before sight threatening disease progresses. The APP retains a history of all ONH images. Future longitudinal analysis will explore the impact of ONH changes to the iKey biometric platform. Translational Relevance: Phones with iKey will host ONH images for biometric protection of both health and financial data. The ONH may be used for automatic screening by new disease detection DNNs. |
| Databáze: | OpenAIRE |
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