Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Hybrid Retinal Image Registration Using Mutual Information and Salient Features

Authors
Ju, JaeyongLoew, MurrayKu, BonhwaKo, Hanseok
Issue Date
Jun-2016
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Keywords
retinal image registration; salient features; mutual information; medical imaging
Citation
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E99D, no.6, pp.1729 - 1732
Indexed
SCIE
SCOPUS
Journal Title
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Volume
E99D
Number
6
Start Page
1729
End Page
1732
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/88576
DOI
10.1587/transinf.2015EDL8265
ISSN
1745-1361
Abstract
This paper presents a method for registering retinal images. Retinal image registration is crucial for the diagnoses and treatments of various eye conditions and diseases such as myopia and diabetic retinopathy. Retinal image registration is challenging because the images have non-uniform contrasts and intensity distributions, as well as having large homogeneous non-vascular regions. This paper provides a new retinal image registration method by effectively combining expectation maximization principal component analysis based mutual information (EMPCA-MI) with salient features. Experimental results show that our method is more efficient and robust than the conventional EMPCA-MI method.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Electrical Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Ko, Han seok photo

Ko, Han seok
College of Engineering (School of Electrical Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE