VISUAL FIELD TESTING USING FORECASTING AND VIRTUAL REALITY

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2022-2

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Bülbül, Emre

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The standard method for assessing a patient’s visual field is visual field testing. Many diseases, including glaucoma, which affects more than 80 million people, require visual field testing for monitoring and diagnosis. The testing is done by sending light to fixed locations with different luminosities while the patient is fixating at a certain point, then the sensitivities to light at each location are determined by recording the responses of the patient to seen stimuli. Because of their form and digital screens, virtual reality headsets have lately begun to be utilized to conduct visual field examinations. However, since the testing duration is long, it causes fatigue in patients, which decreases cooperation and test accuracy. Also, it limits how many tests a clinic can conduct in a day. In this thesis, using a digital screen, the number of testable point locations is increased, and the effect of using an optimal subset of locations, which is found by employing a reinforcement learning method to decrease test duration, is investigated. Also, the effect of using forecasted future visual field test results in testing to the test duration is compared with standard testing strategies.

Subject Keywords

Keywords: Visual Field Testing, Virtual Reality, Perimetry, Forecasting, Reinforcement Learning, Deep Learning

URI

https://hdl.handle.net/11511/96313

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

E. Bülbül, “VISUAL FIELD TESTING USING FORECASTING AND VIRTUAL REALITY,” M.S. - Master of Science, Middle East Technical University, 2022.