Image enhancement of color fundus photographs for age-related macular degeneration: the Shanghai Changfeng Study
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 ana...
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| Published in | International journal of ophthalmology Vol. 15; no. 2; pp. 268 - 275 |
|---|---|
| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
China
International Journal of Ophthalmology Press
18.02.2022
Press of International Journal of Ophthalmology (IJO PRESS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2222-3959 2227-4898 |
| DOI | 10.18240/ijo.2022.02.12 |
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| 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. |
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| AbstractList | 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. 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.AIMTo 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.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.METHODSFundus 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.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.RESULTSA 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.The standardized image optimization software increases diagnostic sensitivity and may help ophthalmologists in AMD diagnosis and screening.CONCLUSIONThe standardized image optimization software increases diagnostic sensitivity and may help ophthalmologists in AMD diagnosis and screening. 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. 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. 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% ( =0.008), specificity decreased slightly from 88% to 84% ( =0.500), and Youden index increased by 0.11. The standardized image optimization software increases diagnostic sensitivity and may help ophthalmologists in AMD diagnosis and screening. 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. |
| Author | Wang, Li-Long Lyu, Chuan-Feng Gao, Xin Zeng, Hai-Luan Shen, Jing-Jing Shen, Min-Qian Chen, Ling-Yan Lin, Huan-Dong Yuan, Yuan-Zhi Liu, Shuo Xie, Guo-Tong |
| AuthorAffiliation | 2 Center for Evidence-based Medicine, Fudan University, Shanghai 200032, China 1 Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai 200032, China 4 Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China 3 Pingan Technology (Shenzhen) Co., Ltd., Shenzhen 518029, Guangdong Province, China 5 Fudan Institute for Metabolic Diseases, Shanghai 200032, China |
| AuthorAffiliation_xml | – name: 2 Center for Evidence-based Medicine, Fudan University, Shanghai 200032, China – name: 3 Pingan Technology (Shenzhen) Co., Ltd., Shenzhen 518029, Guangdong Province, China – name: 1 Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai 200032, China – name: 4 Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China – name: 5 Fudan Institute for Metabolic Diseases, Shanghai 200032, China |
| Author_xml | – sequence: 1 givenname: Jing-Jing surname: Shen fullname: Shen, Jing-Jing – sequence: 2 givenname: Li-Long surname: Wang fullname: Wang, Li-Long – sequence: 3 givenname: Chuan-Feng surname: Lyu fullname: Lyu, Chuan-Feng – sequence: 4 givenname: Shuo surname: Liu fullname: Liu, Shuo – sequence: 5 givenname: Guo-Tong surname: Xie fullname: Xie, Guo-Tong – sequence: 6 givenname: Hai-Luan surname: Zeng fullname: Zeng, Hai-Luan – sequence: 7 givenname: Ling-Yan surname: Chen fullname: Chen, Ling-Yan – sequence: 8 givenname: Min-Qian surname: Shen fullname: Shen, Min-Qian – sequence: 9 givenname: Xin surname: Gao fullname: Gao, Xin – sequence: 10 givenname: Huan-Dong surname: Lin fullname: Lin, Huan-Dong – sequence: 11 givenname: Yuan-Zhi surname: Yuan fullname: Yuan, Yuan-Zhi |
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| Title | Image enhancement of color fundus photographs for age-related macular degeneration: the Shanghai Changfeng Study |
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