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Exudate Detection for Diabetic Retinopathy Using Pretrained Convolutional Neural Networks
Joint Authors
Mateen, Muhammad
Wen, Junhao
Nasrullah, Nasrullah
Sun, Song
Hayat, Shaukat
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-10
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In the field of ophthalmology, diabetic retinopathy (DR) is a major cause of blindness.
DR is based on retinal lesions including exudate.
Exudates have been found to be one of the signs and serious DR anomalies, so the proper detection of these lesions and the treatment should be done immediately to prevent loss of vision.
In this paper, pretrained convolutional neural network- (CNN-) based framework has been proposed for the detection of exudate.
Recently, deep CNNs were individually applied to solve the specific problems.
But, pretrained CNN models with transfer learning can utilize the previous knowledge to solve the other related problems.
In the proposed approach, initially data preprocessing is performed for standardization of exudate patches.
Furthermore, region of interest (ROI) localization is used to localize the features of exudates, and then transfer learning is performed for feature extraction using pretrained CNN models (Inception-v3, Residual Network-50, and Visual Geometry Group Network-19).
Moreover, the fused features from fully connected (FC) layers are fed into the softmax classifier for exudate classification.
The performance of proposed framework has been analyzed using two well-known publicly available databases such as e-Ophtha and DIARETDB1.
The experimental results demonstrate that the proposed pretrained CNN-based framework outperforms the existing techniques for the detection of exudates.
American Psychological Association (APA)
Mateen, Muhammad& Wen, Junhao& Nasrullah, Nasrullah& Sun, Song& Hayat, Shaukat. 2020. Exudate Detection for Diabetic Retinopathy Using Pretrained Convolutional Neural Networks. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142563
Modern Language Association (MLA)
Mateen, Muhammad…[et al.]. Exudate Detection for Diabetic Retinopathy Using Pretrained Convolutional Neural Networks. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1142563
American Medical Association (AMA)
Mateen, Muhammad& Wen, Junhao& Nasrullah, Nasrullah& Sun, Song& Hayat, Shaukat. Exudate Detection for Diabetic Retinopathy Using Pretrained Convolutional Neural Networks. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142563
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142563