Myopia Detection from Eye Fundus Images: New Screening Method Based on You Only Look Once Version 8 † - Rizzieri, Nicola; Dall’Asta, Luca; Ozoliņš, Maris (MDPI, 2024)
Myopia is an eye disorder of global concern due to its increasing prevalence worldwide and its potential to cause sight-threatening conditions. Diagnosis is based on clinical tests such as objective cycloplegic refraction, distance visual acuity, and axial length measurements. Population-based screening is an early detection method that helps prevent uncorrected vision disorders. Advancements in technology and artificial intelligence (AI) applications in the medical field are improving the speed and efficiency of patient care programs. In an effort to provide a new, objective AI-based method for early myopia detection, we developed an algorithm based on the YOLOv8 convolutional neural network, capable of classifying eye fundus images from myopic and non-myopic patients. Preliminary results from an image set obtained from an Italian optometric practice show an overall accuracy of 85.00% and a precision and recall of 88.7% and 91.7%, respectively, in the internal validation dataset. This represents the beginning of a new paradigm, where AI is central to large screening programs aimed at preventing myopia and other avoidable blinding conditions and enabling early diagnosis and management. © 2024 by the authors. --//-- This is an open-access article Rizzieri, N.; Dall’Asta, L.; Ozoliņš, M. Myopia Detection from Eye Fundus Images: New Screening Method Based on You Only Look Once Version 8. Appl. Sci. 2024, 14, 11926. https://doi.org/10.3390/app142411926 published under the CC BY 4.0 licence.
This research was funded by the University of Latvia: support for the payment of the publication from the FAM DSP Doctoral Study Project 2024, Funding code: D-71501Fd-ST-N-100. M.O. was supported by the grant for the Latvian State Emeritus Scientist. Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union's Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART2.
Keywords: Research Subject Categories::NATURAL SCIENCES::Physics; artificial intelligence; eye fundus; fundus image; myopia detection; YOLO