Corneal thickness measurement by secondary speckle tracking and image processing using machine-learning algorithms
| Autor: | Zeev Zalevsky, Yevgeny Beiderman, Avital Moshkovitz, Sergey Agadarov, Uri Polat, Elnatan Davidovitch, Aviya Bennett, Yafim Beiderman |
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| Rok vydání: | 2019 |
| Předmět: |
Adult
Paper Corneal Pachymetry genetic structures Computer science Biomedical Engineering Image processing Tracking (particle physics) 01 natural sciences Imaging law.invention Cornea Machine Learning 010309 optics Biomaterials Young Adult Speckle pattern secondary speckle patterns law Image Interpretation Computer-Assisted 0103 physical sciences Humans Laser beams Aged Measurement method Phantoms Imaging Process (computing) Middle Aged Laser corneal thickness optics eye diseases Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials Neural Networks Computer sense organs Algorithm Algorithms lasers |
| Zdroj: | Journal of Biomedical Optics |
| ISSN: | 1083-3668 |
| DOI: | 10.1117/1.jbo.24.12.126001 |
| Popis: | Corneal thickness (CoT) is an important tool in the evaluation process for several disorders and in the assessment of intraocular pressure. We present a method enabling high-precision measurement of CoT based on secondary speckle tracking and processing of the information by machine-learning (ML) algorithms. The proposed configuration includes capturing by fast camera the laser beam speckle patterns backscattered from the corneal–scleral border, followed by ML processing of the image. The technique was tested on a series of phantoms having different thicknesses as well as in clinical trials on human eyes. The results show high accuracy in determination of eye CoT, and implementation is speedy in comparison with other known measurement methods. |
| Databáze: | OpenAIRE |
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