Image enhancement of color fundus photographs for age-related macular degeneration: the Shanghai Changfeng Study

Author:

Shen Jing-Jing, ,Wang Li-Long,Lyu Chuan-Feng,Liu Shuo,Xie Guo-Tong,Zeng Hai-Luan,Chen Ling-Yan,Shen Min-Qian,Gao Xin,Lin Huan-Dong,Yuan Yuan-Zhi, , , , , , , , , ,

Abstract

AIM: To develop and evaluate a new fundus image optimization software based on red, green, blue channels (RGB) for the evaluation of age-related macular degeneration (AMD) in the Chinese population. METHODS: Fundus images that were diagnosed as AMD from the Shanghai Changfeng Study database were analyzed to develop a standardized optimization procedure. Image brightness, contrast, and color balance were measured. Differences between central lesion area and normal retinal area under different image brightness, contrast, and color balance were observed. The optimal optimization parameters were determined based on the visual system to avoid image distortion. A paired-sample diagnostic test was used to evaluate the enhancement software. Fundus optical coherence tomography (OCT) was used as the gold standard. Diagnostic performances were compared between original images and optimized images using McNemar's test. RESULTS: A fundus image optimization procedure was developed using 86 fundus images of 74 subjects diagnosed with AMD. By observing gray-scale images, choroid can be best displayed in red channel and retina in green channel was found. There was limited information in blue channel. Totally 104 participants were included in the paired sample diagnostic test to assess the performance of the optimization software. After the image enhancement, sensitivity increased from 74% to 88% (P=0.008), specificity decreased slightly from 88% to 84% (P=0.500), and Youden index increased by 0.11. CONCLUSION: The standardized image optimization software increases diagnostic sensitivity and may help ophthalmologists in AMD diagnosis and screening.

Publisher

Press of International Journal of Ophthalmology (IJO Press)

Subject

Ophthalmology

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