Blood Vessels Segmentation in Retinal Fundus Image using Hybrid Method of Frangi Filter, Otsu Thresholding and Morphology

Wiharto ,Ys Palgunadi

doi:10.14569/ijacsa.2019.0100654

Abstract

Diagnosis of computer-based retinopathic hypertension is done by analyzing of retinal images. The analysis is carried out through various stages, one of which is blood vessel segmentation in retinal images. Vascular segmentation of the retina is a complex problem. This is caused by non-uniform lighting, contrast variations and the presence of abnormalities due to disease. This makes segmentation not successful if it only relies on one method. The aims of this study to segment blood vessels in retinal images. The method used is divided into three stages, namely preprocessing, segmentation and testing. The first stage, preprocessing, is to improve image quality with the CLAHE method and the median filter on the green channel image. The second stage, segmenting using a number of methods, namely, frangi filter, 2D-convolution filtering, median filtering, otsu's thresholding, morphology operation, and background subtraction. The last step is testing the system using the DRIVE and STARE dataset. The test results obtained sensitivity 91.187% performance parameters, 86.896% specificity, and area under the curve (AUC) 89.041%. Referring to the performance produced, the proposed model can be used as an alternative for blood vessel segmentation of retinal images.

Highlights

Diagnosis of hypertensive retinopathy can be done by analyzing the retina of the eye
Blood vessel segmentation in the retina is relatively difficult because the retinal image produced by the fundus camera has non-uniform lighting and contrast variations [2]
Another thing that causes difficulty in the process of segmentation is the presence of a disease so that an abnormality will emerge which may be similar to a blood vessel or other sign

Summary

Introduction

Diagnosis of hypertensive retinopathy can be done by analyzing the retina of the eye. Blood vessel segmentation in the retina is relatively difficult because the retinal image produced by the fundus camera has non-uniform lighting and contrast variations [2]. Another thing that causes difficulty in the process of segmentation is the presence of a disease so that an abnormality will emerge which may be similar to a blood vessel or other sign. This condition makes segmentation using one method but a combination of a number of methods.

Methods

Results

Conclusion