Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network
Deep learning of fundus photograph has emerged as a practical and cost-effective technique for automatic screening and diagnosis of severer diabetic retinopathy (DR). The entropy image of luminance of fundus photograph has been demonstrated to increase the detection performance for referable DR usin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Journal of Ophthalmology |
| Online Access: | http://dx.doi.org/10.1155/2020/9139713 |
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| author | Shu-I Pao Hong-Zin Lin Ke-Hung Chien Ming-Cheng Tai Jiann-Torng Chen Gen-Min Lin |
| author_facet | Shu-I Pao Hong-Zin Lin Ke-Hung Chien Ming-Cheng Tai Jiann-Torng Chen Gen-Min Lin |
| author_sort | Shu-I Pao |
| collection | DOAJ |
| description | Deep learning of fundus photograph has emerged as a practical and cost-effective technique for automatic screening and diagnosis of severer diabetic retinopathy (DR). The entropy image of luminance of fundus photograph has been demonstrated to increase the detection performance for referable DR using a convolutional neural network- (CNN-) based system. In this paper, the entropy image computed by using the green component of fundus photograph is proposed. In addition, image enhancement by unsharp masking (UM) is utilized for preprocessing before calculating the entropy images. The bichannel CNN incorporating the features of both the entropy images of the gray level and the green component preprocessed by UM is also proposed to improve the detection performance of referable DR by deep learning. |
| format | Article |
| id | doaj-art-8556522a4fe048e48e9df1aabbfbce04 |
| institution | Kabale University |
| issn | 2090-004X 2090-0058 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Ophthalmology |
| spelling | doaj-art-8556522a4fe048e48e9df1aabbfbce042025-08-20T03:37:47ZengWileyJournal of Ophthalmology2090-004X2090-00582020-01-01202010.1155/2020/91397139139713Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural NetworkShu-I Pao0Hong-Zin Lin1Ke-Hung Chien2Ming-Cheng Tai3Jiann-Torng Chen4Gen-Min Lin5Department of Ophthalmology, Tri-Service General Hospital and National Defense Medical Center, Taipei 114, TaiwanDepartment of Ophthalmology, Buddhist Tzu Chi General Hospital, Hualien 970, TaiwanDepartment of Ophthalmology, Tri-Service General Hospital and National Defense Medical Center, Taipei 114, TaiwanDepartment of Ophthalmology, Tri-Service General Hospital and National Defense Medical Center, Taipei 114, TaiwanDepartment of Ophthalmology, Tri-Service General Hospital and National Defense Medical Center, Taipei 114, TaiwanDepartment of Medicine, Hualien Armed Forces General Hospital, Hualien 971, TaiwanDeep learning of fundus photograph has emerged as a practical and cost-effective technique for automatic screening and diagnosis of severer diabetic retinopathy (DR). The entropy image of luminance of fundus photograph has been demonstrated to increase the detection performance for referable DR using a convolutional neural network- (CNN-) based system. In this paper, the entropy image computed by using the green component of fundus photograph is proposed. In addition, image enhancement by unsharp masking (UM) is utilized for preprocessing before calculating the entropy images. The bichannel CNN incorporating the features of both the entropy images of the gray level and the green component preprocessed by UM is also proposed to improve the detection performance of referable DR by deep learning.http://dx.doi.org/10.1155/2020/9139713 |
| spellingShingle | Shu-I Pao Hong-Zin Lin Ke-Hung Chien Ming-Cheng Tai Jiann-Torng Chen Gen-Min Lin Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network Journal of Ophthalmology |
| title | Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network |
| title_full | Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network |
| title_fullStr | Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network |
| title_full_unstemmed | Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network |
| title_short | Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network |
| title_sort | detection of diabetic retinopathy using bichannel convolutional neural network |
| url | http://dx.doi.org/10.1155/2020/9139713 |
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