Clinically applicable deep learning for diagnosis of diabetic retinopathy

Li Yung-Hui, Yeh Nai-Ning, Kartika Purwandari, Latifa Nabila Harfiya

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

Abstract

Diabetic retinopathy (DR) is the kind of diabetes complication that affects eyes and can damage the blood vessels inside the retina. To diagnose the strength of DR disease based on examination of the retina. Nowadays, the common diagnosis process asks for experienced ophthalmologists to inspect both fundus image and OCT (optical coherence tomography) images, which is time-consuming and not very convenient for remote rural inhabitants. The research purpose in this paper is to propose a new paradigm of automatic DR diagnosis by using artificial intelligence and cloud computing. Inside the DCNN, we changed max-pooling layers with factional max-pooling. We trained using support vector machine (SVM) to learn the underlying boundary of distribution of each category. Using that proposed method, we achieved the results of the recognition up to 86.17%. We also develop an iPhone APP. It called 'Deep Retina' that equipped with a handheld ophthalmoscope, a layman can take fundus images and perform the diagnosis automatically without intervention from ophthalmologists. It is a practically applicable telemedicine system which benefits the home care, remote medical care, and self-examination.

Original languageEnglish
Title of host publicationProceedings - 2019 12th International Conference on Ubi-Media Computing, Ubi-Media 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages124-129
Number of pages6
ISBN (Electronic)9781728128207
DOIs
StatePublished - Aug 2019
Event12th International Conference on Ubi-Media Computing, Ubi-Media 2019 - Bali, Indonesia
Duration: 6 Aug 20199 Aug 2019

Publication series

NameProceedings - 2019 12th International Conference on Ubi-Media Computing, Ubi-Media 2019

Conference

Conference12th International Conference on Ubi-Media Computing, Ubi-Media 2019
Country/TerritoryIndonesia
CityBali
Period6/08/199/08/19

Keywords

  • CNN
  • Deep learning
  • Diabetic retinopathy
  • SVM
  • TLBO

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