Retinal Blood Vessels and Optic Disc Segmentation Using U-Net

S. Alex David,Adi Alhudhaif,V. Dhilip Kumar,Majid Nour,C. Mahesh,Kemal Polat,Nagarajan DEIVANAYAGAMPILLAI

doi:10.1155/2022/8030954

Abstract

A color fundus image is a photograph obtained using a fundus camera of the inner wall of the eyeball. In the image, doctors may see changes in the retinal vessels, which can be used to diagnose various dangerous disorders such as arteriosclerosis, some macular degeneration related to age, and glaucoma. To diagnose certain disorders as early as possible, automatic segmentation of retinal arteries is used to help the doctors. Also, it is a challenge for the medical community to analyze the image with the right procedure to diagnose the disorders with high accuracy. Furthermore, this will help the doctor to make the right decision on effective treatment. Hence, the authors have implemented an enhanced architecture called U-Net to segment retinal vessels in this paper. The proposed conventional U-Net permits using all the accessible spatial setting information by adding the multiscale input layer and a thick square to the conventional U-Net in terms of improving the accuracy level of image segmentation. It achieved 95.6% accuracy with a comparatively traditional U-Net model. Moreover, the segmentation results have proved that the proposed approach outperformed in detecting most complex low-contrast blood vessels even when they are very thin. The task of segmenting vessels in retinal images is known as retinal vessel segmentation. Blood vessel density can be assessed using dense pixel values. Data augmentation and analytics play a major role in building the true value of eye blood vessels for medical diagnosis. The proposed method is very promising in the automatic segmentation of retinal arteries.

Highlights

A special fundus camera is used to photograph the color fundus image, which is the inside and back surface of the eyeball. e picture is obtained in a painless and noninvasive manner
Some of the retinal nerve fibers present in the oculus dexter (OD) transfer the images taken from the eyeball first converted into visual signals and transferred immediately to the head of the body called the brain. e cells in the retina called photoreceptors are found in the OD of the retina, which aid vision. e “blind spot,” as the OD dubbed it, was created as a result of this. e brightest area of the retina is oculentum (OC) [4], which is located at the innermost part of the OD [5]
To identify the effect of glaucoma in the eye, different models of eye images are captured such as the fundus image by using various methods such as magnetic resonance imaging (MRI) and optical coherence tomography (OCT); in glaucoma detection, fundus pictures are one of the most suggested methodologies. ese are the eye images taken using a camera known as a fundus camera

Summary

Introduction

A special fundus camera is used to photograph the color fundus image, which is the inside and back surface of the eyeball. e picture is obtained in a painless and noninvasive manner. A special fundus camera is used to photograph the color fundus image, which is the inside and back surface of the eyeball. Retinal vascular alterations that can be used to diagnose various significant disorders such as macular degeneration, arteriosclerosis, and glaucoma [1] can be identified. Some of the retinal nerve fibers present in the oculus dexter (OD) transfer the images taken from the eyeball first converted into visual signals and transferred immediately to the head of the body called the brain. Ese are the eye images taken using a camera known as a fundus camera. Other elements such as the veins, optic cup and disc, fovea, macula, artery, and other retinas will be portrayed in fundus images [6]. It has been demonstrated that using the fundus images, ocular illnesses can be anticipated quickly

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