Prediction of diseases in retinal fundus images using image processing
Author(s):
Sushmitha C, Saranya V, Keerthana K
Keywords:
Retinal image registration, optimal transport, Blood vessel detection, Image alignment
Abstract
The optimal transport theory enables great flexibility in modeling problems associated with image registration, as different optimization resources successfully used because the choice of suitable matching models to align the pictures. The proposed method in this paper is an automated framework for multimodal fundus image registration using both colored and gray scaled images and graph matching schemes into a functional and easy method. Then, this method is used to predict the diseases accurately. Then this method is also used to predict whether the disease is affected or not affected by using a comparative method. These methodologies are validated by a comprehensive set of comparisons against competing and well-established image registration methods, by using real medical datasets and classic measures typically employed as a benchmark by the medical imaging community our proposed method is mostly used in medical field. It is used to easily detect the diseases. We demonstrate the accuracy and effectiveness of this framework throughout a comprehensive set of qualitative and quantitative comparisons against several influential state-of -the- art methods on various fundus image databases.
Article Details
Unique Paper ID: 149636

Publication Volume & Issue: Volume 7, Issue 1

Page(s): 169 - 175
Article Preview & Download


Share This Article

Go To Issue



Call For Paper

Volume 7 Issue 3

Last Date 25 August 2020

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies