Hybrid retinal image registration using mutual information and salient features

Jaeyong Ju, Murray Loew, Bonhwa Ku, Hanseok Ko

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1729-1732
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE99D
Issue number6
DOIs
Publication statusPublished - 2016 Jun 1

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Keywords

  • Medical Imaging
  • Mutual Information
  • Retinal Image Registration
  • Salient Features

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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