Evaluating color efficacy in fundus photography for artificial intelligence classification of retinopathy of prematurity

Behrouz Ebrahimi; David Le; Mansour Abtahi; Albert K. Dadzie; Alfa Rossi; Mojtaba Rahimi; Taeyoon Son; Susan Ostmo; J. Peter Campbell; R. V. Paul Chan; Xincheng Yao

doi:10.1117/12.3003192

12 March 2024 Evaluating color efficacy in fundus photography for artificial intelligence classification of retinopathy of prematurity

Behrouz Ebrahimi, David Le, Mansour Abtahi, Albert K. Dadzie, Alfa Rossi, Mojtaba Rahimi, Taeyoon Son, Susan Ostmo, J. Peter Campbell, R. V. Paul Chan, Xincheng Yao

Author Affiliations +

Proceedings Volume 12824, Ophthalmic Technologies XXXIV; 128240O (2024) https://doi.org/10.1117/12.3003192
Event: SPIE BiOS, 2024, San Francisco, California, United States

Conference Poster

Abstract

This study investigates the efficacy of the red, green, and blue channels in color fundus photography on the deep learning classification of retinopathy of prematurity (ROP). We used a total of 200 color fundus images from four ROP stages and applied the transfer learning for deep learning classification. To enhance visibility, contrast limiting adaptive histogram equalization (CLAHE) was utilized. Multi-color-channel fusion approach was tested to determine its effect on ROP classification. For individual channel classification, the green channel demonstrated the best results, with an accuracy of 80.5%, sensitivity of 61%, and specificity of 87%. Multi-color-channel fusion provided slightly better performance than green channel with an accuracy of 81%, sensitivity of 62%, and specificity of 87.33%. After CLAHE, the red-only, green-only, and RGB-fusion showed comparable performance, with accuracies of 83.5%, 84%, and 84.25, sensitivities of 67%, 68% and 68.5%, and specificities of 89%, 89.33% and 89.50%, respectively. This observation suggests that the red channel after contrast enhancement can provide sufficient information for ROP stage classification.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Behrouz Ebrahimi, David Le, Mansour Abtahi, Albert K. Dadzie, Alfa Rossi, Mojtaba Rahimi, Taeyoon Son, Susan Ostmo, J. Peter Campbell, R. V. Paul Chan, and Xincheng Yao "Evaluating color efficacy in fundus photography for artificial intelligence classification of retinopathy of prematurity", Proc. SPIE 12824, Ophthalmic Technologies XXXIV, 128240O (12 March 2024); https://doi.org/10.1117/12.3003192

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