Restricted Boltzmann Machines for Fundus Image Reconstruction and Classification of Hypertension Retinopathy

Bambang Krismono Triwijoyo, Boy Subirosa Sabarguna, Widodo Budiharto, Edi Abdurachman

Research output: Contribution to journalArticlepeer-review

Abstract

Conventionally classification of hypertensive retinopathy through analysis of fundus images by experts, but this method the results are highly dependent on the accuracy of observations and expert experience. In this study, we propose a fundus image reconstruction and Hypertensive retinopathy classification model using Restricted Boltzmann Machines (RBM), as well as the Messidor database that has been labeled as a dataset. The experimental results show that the performance of the model produces an accuracy level of 99.05% where the model can generalize image input into one of the nine classes of the severity of hypertension retinopathy.

Original languageEnglish
Pages (from-to)156-166
Number of pages11
JournalJournal of Computer Science
Volume17
Issue number2
DOIs
Publication statusPublished - 2021

Keywords

  • Classification
  • Fundus Image
  • Hypertensive Retinopathy
  • Reconstruction
  • Restricted Boltzmann Machines

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