Detection and quantification of highly reflective particulate lesions (HRF) in retinal patients

Abstract

A method for identifying highly reflective particulate lesions (HRFs) in a patient's eye includes accessing one or more optical coherence tomography (OCT) scans of a retina of the patient's eye and inputting the one or more OCT scans into one or more machine learning models trained to segment the one or more OCT scans and identify a set of highly reflective entities detectable from the one or more OCT scans. The method further includes determining one or more diameter measurements corresponding to each highly reflective entity in the set of identified highly reflective entities based on the segmented one or more OCT scans, and identifying highly reflective particulate lesions (HRFs) in the retina of the patient's eye based on whether at least one of the one or more diameter measurements meets a diameter threshold.

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