Detection of hypertensive retinopathy using principal component analysis (PCA) and backpropagation neural network methods

Rahmat Arasy, Basari

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

Abstract

Hypertensive Retinopathy (HTR) is a disease caused by high blood pressure flowing into the retinal blood vessels, resulting in thickening of blood vessel walls and reducing blood flow in the retina. Complications arising from this disease are diverse and dangerous, ranging from retinal vein occlusion, eye nerve damage, even blindness. This paper proposed a system for hypertensive retinopathy detection by using Principal Component Analysis (PCA) dan Backpropagation Neural Network (BNN). Retinal image was taken from STARE database which separated into learning and testing data with a ratio 7 to 3. PCA as fundus-image-dimension-reduction method has successfully reduced fundus image raw data by 99.9% reduction, thus cutting computation load for neural network training. This paper presented Backpropagation Neural Network (BNN) as main classification algorithm which done by setting its parameters, learning and testing the data. So the model could classify retinal image into one of two classes, namely the normal retina and retina with high blood pressure, based on the BNN output result. The proposed model result showed that testing accuracy up to 86.36%.

Original languageEnglish
Title of host publication3rd Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices
Subtitle of host publicationProceedings of the International Symposium of Biomedical Engineering, ISBE 2018
EditorsPraswasti P.D.K. Wulan, Misri Gozan, Sotya Astutiningsih, Ghiska Ramahdita, Radon Dhelika, Prasetyanugraheni Kreshanti
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418226
DOIs
Publication statusPublished - 9 Apr 2019
Event3rd International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2018 - Jakarta, Indonesia
Duration: 6 Aug 20188 Aug 2018

Publication series

NameAIP Conference Proceedings
Volume2092
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2018
CountryIndonesia
CityJakarta
Period6/08/188/08/18

Keywords

  • Backpropagation Neural Network
  • Hypertensive Retinopathy
  • Principal Component Analysis
  • Retina

Fingerprint Dive into the research topics of 'Detection of hypertensive retinopathy using principal component analysis (PCA) and backpropagation neural network methods'. Together they form a unique fingerprint.

Cite this