Registration of color and OCT fundus images using low-dimensional step pattern analysis

Jimmy Addison Lee, Jun Cheng, Guozhen Xu, Ee Ping Ong, Beng Hai Lee, Damon Wing Kee Wong, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Existing feature descriptor-based methods on retinal image registration are mainly based on scale-invariant feature transform (SIFT) or partial intensity invariant feature descriptor (PIIFD). While these descriptors are many times being exploited, they have not been applied to color fundus and optical coherence tomography (OCT) fundus image pairs. OCT fundus images are challenging to register as they are often degraded by speckle noise. The descriptors also demand high dimensionality to adequately represent the features of interest. To this end, this paper presents a registration algorithm coined low-dimensional step pattern analysis (LoSPA), tailored to achieve low dimensionality while providing sufficient distinctiveness to effectively register OCT fundus images with color fundus photographs. The algorithm locates hypotheses of robust corner features based on connecting edges from the edge maps, mainly formed by vascular junctions. It continues with describing the corner features in a rotation invariant manner using step patterns. These customized step patterns are insensitive to intensity changes. We conduct comparative evaluation and LoSPA achieves a higher success rate in registration when compared to the state-of-the-art algorithms.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings
EditorsJoachim Hornegger, Alejandro F. Frangi, William M. Wells, Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, Nassir Navab, William M. Wells, William M. Wells, Alejandro F. Frangi, Joachim Hornegger, Nassir Navab
PublisherSpringer Verlag
Pages214-221
Number of pages8
ISBN (Print)9783319245706, 9783319245706, 9783319245706
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: 5 Oct 20159 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9350
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Country/TerritoryGermany
CityMunich
Period5/10/159/10/15

Keywords

  • Feature descriptor
  • LoSPA
  • Optical coherence tomography
  • Registration

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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