Classification of diabetic retinopathy and normal retinal images using CNN and SVM

Dinial Utami Nurul Qomariah, Handayani Tjandrasa, Chastine Fatichah

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

78 Citations (Scopus)

Abstract

Diabetic retinopathy is a disease caused by chronic diabetes and can cause blindness. Therefore early detection of diabetic retinopathy is essential to prevent the increased severity. An automated system can help detect diabetic retinopathy quickly for determining the follow-up treatment to avoid further damage to the retina. This study proposes a deep learning method for extracting features and classification using a support vector machine. We use the high-level features of the last fully connected layer based on transfer learning from Convolutional Neural Network (CNN) as the input features for classification using the support vector machine (SVM). This method reduces the computation time required by the classification process using CNN with fine-tuning. The proposed method is tested using 77 and 70 retinal images from Messidor database of base 12 and base 13 respectively. From the results of the experiments, the highest accuracy values are 95.83% and 95.24% for base 12 and base 13 respectively.

Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages152-157
Number of pages6
ISBN (Electronic)9781728121338
DOIs
Publication statusPublished - Jul 2019
Event12th International Conference on Information and Communication Technology and Systems, ICTS 2019 - Surabaya, Indonesia
Duration: 18 Jul 2019 → …

Publication series

NameProceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019

Conference

Conference12th International Conference on Information and Communication Technology and Systems, ICTS 2019
Country/TerritoryIndonesia
CitySurabaya
Period18/07/19 → …

Keywords

  • CNN
  • Diabetic Retinopathy
  • Retinal Fundus Images
  • SVM
  • Transfer Learning

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