Open AccessThe review of computer aided diagnostic hypertensive retinopathy based on the retinal image processing
Author(s) -
Wiharto Wiharto,
Esti Suryani
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/620/1/012099
Subject(s) - hypertensive retinopathy , fundus (uterus) , computer science , diabetic retinopathy , retinopathy , feature extraction , segmentation , artificial intelligence , image processing , retina , automation , medicine , computer aided diagnosis , feature (linguistics) , image segmentation , disease , ophthalmology , pattern recognition (psychology) , pathology , image (mathematics) , diabetes mellitus , mechanical engineering , linguistics , philosophy , physics , engineering , optics , endocrinology
Hypertensive retinopathy is a disease caused by acute high blood pressure. Examination of the disease can be done by analyzing the retina of the eye. Analysis can be done automatically by using the image processing of the retina from fundus cameras. The automation model is widely developed by combining a number of segmentation methods, classification algorithms and feature extraction. Unfortunately no one has reviewed a number of existing studies on the diagnosis of hypertensive retinopathy. In this study aims to conduct a review of a number of studies in the period 2010-2018 on the diagnosis of hypertensive retinopathy. The focus of the review is on the method of segmentation, feature extraction, and the classification algorithm used in the diagnostic model of hypertensive retinopathy. The review also includes comparisons of a number of diagnostic models that have been developed, and suggestions for further model development.