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Automated Identification of Glaucoma from Fundus Images using Deep learning Techniques

    Authors

    • Ajitha S 1
    • Dr. M V Judy 2
    • Dr. Meera N 3
    • Dr. Rohith N 4

    1 Research Scholar, Department of Computer Applications, Cochin University of Science and Technology, India,

    2 Associate Professor, Department of Computer Applications, Cochin University of Science and Technology, India,

    3 Junior Resident, Government Medical College, Surat, Gujarat, India

    4 House Surgeon, Government Medical College, Kozhikode, Kerala, India

,

Document Type : Research Article

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Abstract

Glaucoma has arisen as the one of the main sources of visual impairment. A typical technique for diagnosing glaucoma is through assessment optic nerve head by an experienced ophthalmologist. This methodology is arduous and burns-through a lot of time. Despite the fact that the analysis of this infection has not yet been discovered, the period of primary identification can preserve from the glaucoma. Subsequently, customary glaucoma screening is basic and suggested. The issue can be settled by applying machine learning techniques for glaucoma detection. We present an automated glaucoma screening framework using a pre-trained Alexnet model with SVM classifier to enhance the classification accuracy . In this study, we used three publicly available dataset as HRF, Origa and Drishti_GS1 dataset. The proposed model achieved the image classification accuracy of 91.21%. This study showed that using pre-trained CNN with SVM for glaucoma detection showed greater accuracy in automatic image classification than just CNN or SVM.

Keywords

  • glaucoma
  • Feature Extraction
  • Support Vector Machine
  • Convolution Neural Network
  • AlexNet
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European Journal of Molecular & Clinical Medicine
Volume 7, Issue 2
November 2020
Page 5449-5458
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  • Article View: 465
  • PDF Download: 527

APA

S, A., Judy, D. M. V., N, D. M., & N, D. R. (2020). Automated Identification of Glaucoma from Fundus Images using Deep learning Techniques. European Journal of Molecular & Clinical Medicine, 7(2), 5449-5458.

MLA

Ajitha S; Dr. M V Judy; Dr. Meera N; Dr. Rohith N. "Automated Identification of Glaucoma from Fundus Images using Deep learning Techniques". European Journal of Molecular & Clinical Medicine, 7, 2, 2020, 5449-5458.

HARVARD

S, A., Judy, D. M. V., N, D. M., N, D. R. (2020). 'Automated Identification of Glaucoma from Fundus Images using Deep learning Techniques', European Journal of Molecular & Clinical Medicine, 7(2), pp. 5449-5458.

VANCOUVER

S, A., Judy, D. M. V., N, D. M., N, D. R. Automated Identification of Glaucoma from Fundus Images using Deep learning Techniques. European Journal of Molecular & Clinical Medicine, 2020; 7(2): 5449-5458.

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