Retinal Blood Vessels Segmentation Using Deep Learning Model-A Review

This paper deals with a complete survey of the techniques and medical applications of retinal image analysis using deep learning. Mostly eye ailments very often lead to loss of sight if proper diagnosis and treatment is not given. For instance, diabetic retinopathy (DR) is one disease where the reti...

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Bibliographic Details
Main Authors: Babu, A.Anand, Jegathesan, V., David, D.Jasmine, Suriya, K S
Format: Conference Proceeding
Language:English
Subjects:
Blood vessels
Deep learning
fundus images
Image analysis
Image segmentation
neural networks
Retina
Retinal images
retinal vessels
Retinopathy
segmentation
Visualization
Online Access:Request full text
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Summary:This paper deals with a complete survey of the techniques and medical applications of retinal image analysis using deep learning. Mostly eye ailments very often lead to loss of sight if proper diagnosis and treatment is not given. For instance, diabetic retinopathy (DR) is one disease where the retinal blood vessels of eyes were damaged. On the basics of the professional knowledge, the ophthalmologists will diagnose diabetic retinopathy. Advancement in image processing and artificial intelligence (AI), the methods like computer vision are applied in medical image analysis. These techniques utilize the accurate visual analysis to notify the irregularity in the blood vessels. Recently machine learning techniques in particular the deep learning techniques have been implemented successfully in this domain. This paper focused the recent advancement in deep learning models for the analysis of retinal images. This paper organizes the deep learning-based segmentation methods with its limitations and advantages. In the end recommendations were given for future improvement in analyzing the retinal images.
ISSN:2644-1802
DOI:10.1109/ICDCS54290.2022.9780680