Registration of OCT fundus images with color fundus photographs based on blood vessel ridges

This paper proposes an algorithm to register OCT fundus images (OFIs) with color fundus photographs (CFPs). This makes it possible to correlate retinal features across the different imaging modalities. Blood vessel ridges are taken as features for registration. A specially defined distance, incorpor...

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Main Authors:	Li, Ying, Gregori, Giovanni, Knighton, Robert W., Lujan, Brandon J., Rosenfeld, Philip J.
Format:	Online
Language:	English
Published:	Optical Society of America 2010
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368356/

id	pubmed-3368356
recordtype	oai_dc
spelling	pubmed-33683562012-10-01 Registration of OCT fundus images with color fundus photographs based on blood vessel ridges Li, Ying Gregori, Giovanni Knighton, Robert W. Lujan, Brandon J. Rosenfeld, Philip J. Research-Article This paper proposes an algorithm to register OCT fundus images (OFIs) with color fundus photographs (CFPs). This makes it possible to correlate retinal features across the different imaging modalities. Blood vessel ridges are taken as features for registration. A specially defined distance, incorporating information of normal direction of blood vessel ridge pixels, is designed to calculate the distance between each pair of pixels to be matched in the pair image. Based on this distance a similarity function between the pair image is defined. Brute force search is used for a coarse registration and then an Iterative Closest Point (ICP) algorithm for a more accurate registration. The registration algorithm was tested on a sample set containing images of both normal eyes and eyes with pathologies. Three transformation models (similarity, affine and quadratic models) were tested on all image pairs respectively. The experimental results showed that the registration algorithm worked well. The average root mean square errors for the affine model are 31 µm (normal) and 59 µm (eyes with disease). The proposed algorithm can be easily adapted to registration for other modality retinal images. Optical Society of America 2010-12-20 /pmc/articles/PMC3368356/ /pubmed/21263537 http://dx.doi.org/10.1364/OE.19.000007 Text en ©2011 Optical Society of America http://creativecommons.org/licenses/by-nc-nd/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License, which permits download and redistribution, provided that the original work is properly cited. This license restricts the article from being modified or used commercially.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Li, Ying Gregori, Giovanni Knighton, Robert W. Lujan, Brandon J. Rosenfeld, Philip J.
spellingShingle	Li, Ying Gregori, Giovanni Knighton, Robert W. Lujan, Brandon J. Rosenfeld, Philip J. Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
author_facet	Li, Ying Gregori, Giovanni Knighton, Robert W. Lujan, Brandon J. Rosenfeld, Philip J.
author_sort	Li, Ying
title	Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
title_short	Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
title_full	Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
title_fullStr	Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
title_full_unstemmed	Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
title_sort	registration of oct fundus images with color fundus photographs based on blood vessel ridges
description	This paper proposes an algorithm to register OCT fundus images (OFIs) with color fundus photographs (CFPs). This makes it possible to correlate retinal features across the different imaging modalities. Blood vessel ridges are taken as features for registration. A specially defined distance, incorporating information of normal direction of blood vessel ridge pixels, is designed to calculate the distance between each pair of pixels to be matched in the pair image. Based on this distance a similarity function between the pair image is defined. Brute force search is used for a coarse registration and then an Iterative Closest Point (ICP) algorithm for a more accurate registration. The registration algorithm was tested on a sample set containing images of both normal eyes and eyes with pathologies. Three transformation models (similarity, affine and quadratic models) were tested on all image pairs respectively. The experimental results showed that the registration algorithm worked well. The average root mean square errors for the affine model are 31 µm (normal) and 59 µm (eyes with disease). The proposed algorithm can be easily adapted to registration for other modality retinal images.
publisher	Optical Society of America
publishDate	2010
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368356/
_version_	1611534910223286272

Registration of OCT fundus images with color fundus photographs based on blood vessel ridges

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