Validating a computer aided glaucoma screening system using RIGA 2 dataset

Ahmed Almazroa; Mohammed Alawawd

doi:10.1117/12.2580509

15 February 2021 Validating a computer aided glaucoma screening system using RIGA 2 dataset

Ahmed Almazroa, Mohammed Alawawd

Proceedings Volume 11601, Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications; 1160112 (2021) https://doi.org/10.1117/12.2580509
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

The purpose of this study was to evaluate the ability of a developed computer aided glaucoma screening system to screen for glaucoma using a Food Drug Administration (FDA) Class II diagnostic digital fundus photography system used for diabetic retinopathy screening (DRS). The fundus photos collected from participants underwent a comprehensive eye examination as well as non-mydriatic 45° single photograph retinal imaging centered on the macula. Optic nerve images within the 45° non-mydriatic and non-stereo DRS images (The Retinal fundus Images for Glaucoma Analysis: the RIGA2 dataset) were evaluated by a computer-aided automated segmentation system to determine the vertical cup-to-disc ratio (VCDR). The VCDR from clinical assessment was considered as gold standard, VCDR results from the computer system was compared to that from clinical assessment. The grading agreement was assessed by computing intraclass correlation coefficient (ICC). In addition, sensitivity and specificity were calculated. Among 245 fundus photos, 166 images met quality specifications for analysis. The ICC value for the VCDR between the gold standard clinical exam and the automated segmentation system was 0.41, indicating fair agreement. The specificity and sensitivity for (0.6 VCDR) were 76% and 47% respectively.

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Citation Download Citation

Ahmed Almazroa and Mohammed Alawawd "Validating a computer aided glaucoma screening system using RIGA 2 dataset", Proc. SPIE 11601, Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications, 1160112 (15 February 2021); https://doi.org/10.1117/12.2580509

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