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Building a Language Data Set in Telugu Using Machine Learning Techniques to Address Suicidal Ideation and Behaviors in Adolescents Read chapter Read first chapter

2021 | OriginalPaper | Chapter

A Review: Hemorrhage Detection Methodologies on the Retinal Fundus Image

Authors : Niladri Sekhar Datta, Koushik Majumder, Amritayan Chatterjee, Himadri Sekhar Dutta, Sumana Chatterjee

Published in: Applications of Artificial Intelligence and Machine Learning

Publisher: Springer Singapore

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Abstract

Diabetic retinopathy (DR) is a microvascular symptom where retina is affected by fluid leaks of the fragile blood vessels. Clinically, retinal Hemorrhages are one of the earliest indications of diabetic retinopathy disease. In this contrast, the Hemorrhage count is used to indicate the severity of this disease. The early detection of retinal Hemorrhages obviously prevents the incurable blindness of the DR patients. But, retinal Hemorrhage detection is still a challenging task. Highly reliable, accurate, platform independent retinal Hemorrhage detection method is still an open field. In this research article, we have reviewed the principal methodologies which are used to diagnose the retinal Hemorrhages under the diabetic retinopathy screening operations. This review article helps the researchers to develop a high quality retinal Hemorrhage screening method in future.

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previous chapter Static Video Summarization: A Comparative Study of Clustering-Based Techniques
next chapter A Study on Retinal Image Preprocessing Methods for the Automated Diabetic Retinopathy Screening Operation
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Metadata
Title
A Review: Hemorrhage Detection Methodologies on the Retinal Fundus Image
Authors
Niladri Sekhar Datta
Koushik Majumder
Amritayan Chatterjee
Himadri Sekhar Dutta
Sumana Chatterjee
Copyright Year
2021
Publisher
Springer Singapore
Book
Applications of Artificial Intelligence and Machine Learning

Print ISBN: 978-981-16-3066-8

Electronic ISBN: 978-981-16-3067-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-16-3067-5_27

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