IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Automatic Screening of Diabetic Maculopathy Using Image Processing: A Survey

Automatic Screening of Diabetic Maculopathy Using Image Processing: A Survey
View Sample PDF
Author(s): Shweta Reddy (Visvesvaraya Technological University, Gulbarga, India)
Copyright: 2023
Pages: 8
Source title: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-7544-7.ch083

Purchase

View Automatic Screening of Diabetic Maculopathy Using Image Processing: A Survey on the publisher's website for pricing and purchasing information.

Abstract

Retinal imaging is a challenging screening method for detection of retinal abnormalities. Diabetic Maculopathy (DM) is a condition that can result from retinopathy. Regular screening is necessary for diabetic maculopathy in order to identify the risk of vision loss. Maculopathy is damage to macula, the key region responsible for high sharp colour vision. Diabetic Retinopathy and Diabetic Maculopathy needs regular observation in order to indicate visual impairment risk. In this article, the author first presents a brief summary of diabetic maculopathy and its causes. Then, an exhaustive literature review of different automated DM diagnosis systems offered. It is important for ophthalmologists to have an automated system which detects early symptoms of the disease and yields a high accurate result. A vital assessment of the image processing techniques used for DM feature detection is projected in this paper. Various methods have been proposed to identify and classify DM based on severity level.

Related Content

Aylin Gökhan, Kubilay Dogan Kilic, Türker Çavuşoğlu, Yiğit Uyanıkgil. © 2024. 12 pages.
Pratyush Panda, Subhalaxmi Das. © 2024. 21 pages.
Vikram Singh, Sangeeta Rani. © 2024. 17 pages.
Pancham Singh, Mrignainy Kansal, Shirshendu Lahiri, Harshit Vishnoi, Lakshay Mittal. © 2024. 19 pages.
Shreeharsha Dash, Subhalaxmi Das. © 2024. 16 pages.
V. Sathya, Shalini Parthiban, M. Megavarshini, V. Shenbagaraman, R. Ramya. © 2024. 13 pages.
Olalekan Joel Awujoola, Theophilus Enem Aniemeka, Oluwasegun Abiodun Abioye, Abidemi Elizabeth Awujoola, Fiyinfoluwa Ajakaiye, Olayinka Racheal Adelegan. © 2024. 34 pages.
Body Bottom