Automatic Grading of Retinal Blood Vessel in Deep Retinal Image Diagnosis
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IMAGE & SIGNAL PROCESSING
Automatic Grading of Retinal Blood Vessel in Deep Retinal Image Diagnosis Debasis Maji1 · Arif Ahmed Sekh2 Received: 21 April 2020 / Accepted: 3 August 2020 © The Author(s) 2020
Abstract Automatic grading of retinal blood vessels from fundus image can be a useful tool for diagnosis, planning and treatment of eye. Automatic diagnosis of retinal images for early detection of glaucoma, stroke, and blindness is emerging in intelligent health care system. The method primarily depends on various abnormal signs, such as area of hard exudates, area of blood vessels, bifurcation points, texture, and entropies. The development of an automated screening system based on vessel width, tortuosity, and vessel branching are also used for grading. However, the automated method that directly can come to a decision by taking the fundus images got less attention. Detecting eye problems based on the tortuosity of the vessel from fundus images is a complicated task for opthalmologists. So automated grading algorithm using deep learning can be most valuable for grading retinal health. The aim of this work is to develop an automatic computer aided diagnosis system to solve the problem. This work approaches to achieve an automatic grading method that is opted using Convolutional Neural Network (CNN) model. In this work we have studied the state-of-the-art machine learning algorithms and proposed an attention network which can grade retinal images. The proposed method is validated on a public dataset EIARG1, which is only publicly available dataset for such task as per our knowledge. Keywords Diabetic retinopathy (DR) · Retinopathy of prematurity (ROP) · Tortuosity-based grading
Introduction The major cause of poor eye health is Diabetes. This is a dangerous malady, which not only affect the human eye but also the cause of several heart problems. In many cases the main cause of blindness is diabetic retinopathy (DR) [1, 2]. Diabetic retinopathy (die-uhBET-ik ret-ih-NOP-uh-thee) is caused by long term diabetes that affects eyes. It’s caused by damaging the blood vessels of the light-sensitive tissue at the back of the eye (retina)[3]. In ophthalmology, retinal picture examination is a helpful instrument for the non-invasive This article is part of the Topical Collection on Image & Signal Processing Arif Ahmed Sekh
[email protected] Debasis Maji [email protected] 1
Haldia Institute of Technology, Haldia, India
2
UiT The Arctic University of Norway, Tromsø, Norway
determination of numerous important illnesses, for example, hypertension, diabetes or atherosclerosis. Basic side effects of those pathologies incorporate neovascularization, event of obsessive structures, or expanded tortuosity that can be watched examining the vascular tree of the eye fundus [4]. Early prognosis of DR can prevent many complicated health issues including blindness. The process begins with the analysis of rear of an eye; also known as the fundus. The images are captured using specialized fundus cameras consisting of an i
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