Retinal Fundus Image Research for Diagnosis of Diabetic Maculopathy release_wfm4ez6u4zbv7powdxxjgzy3di

Published in International journal of recent technology and engineering by Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP.

2019   Issue 2S11, p339-347

Abstract

Fundus images are valuable resources in diagnosis of retinal diseases. This paper proposes a computer-aided method based on various feature extraction techniques and support vector machines (SVM) for detection and classification of diabetic maculopathy (DM). DM, defined as retinopathy within one disc diameter of the centre of the macula, is a major cause of sight loss in diabetes. Here, we bring out a new approach to detect DM based on retinal fundus image features. During the first stage the input image is enhanced and the optic disc is masked to determine the presence of regions of foveal neighborhood. The second stage, deals with various feature extraction technique based on transform, shape and texture features. Extracted features are further categorized as healthy or affected images. Here we go for classification task using the RBF Support Vector Machine (SVM) classification, the techniques have been tested on retinal databases and these are compared with trained phase to categorize Healthy and DM images. This method can detect DM with a level accuracy on par with human retinal specialists
In application/xml+jats format

Archived Files and Locations

application/pdf  639.3 kB
file_2t7tu6stovcbzgsgiynnnykity
www.ijrte.org (publisher)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2019-11-02
Language   en ?
Journal Metadata
Open Access Publication
Not in DOAJ
In ISSN ROAD
Not in Keepers Registry
ISSN-L:  2277-3878
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: d0076fe9-d53c-440d-b1fd-9ea69577faae
API URL: JSON