A1 Journal article (refereed), original research

Comparison of image registration methods for composing spectral retinal images


Publication Details

Authors: Laaksonen Lauri, Claridge Ela, Fält Pauli, Hauta-Kasari Markku, Uusitalo Hannu, Lensu Lasse

Publisher: Elsevier

Publication year: 2017

Language: English

Related journal or series: Biomedical Signal Processing and Control

Journal name in source: Biomedical Signal Processing and Control

Volume number: 36

Start page: 234

End page: 245

Number of pages: 12

ISSN: 1746-8094

JUFO level of this publication: 1

Digital Object Identifier (DOI): http://dx.doi.org/10.1016/j.bspc.2017.03.003

Permanent website address: https://api.elsevier.com/content/abstract/scopus_id/85018791035

Open Access: Not an Open Access publication


Abstract

Spectral retinal images have
significant potential for improving the early detection and
visualization of subtle changes due to eye diseases and many systemic
diseases. High resolution in both the spatial and the spectral domain
can be achieved by capturing a set of narrow-band channel images from
which the spectral images are composed. With imaging techniques where
the eye movement between the acquisition of the images is unavoidable,
image registration is required. As manual registration of the channel
images is laborious and prone to error, a suitable automatic
registration method is necessary.

In this paper, the
applicability of a set of image registration methods for the
composition of spectral retinal images is studied. The registration
methods are quantitatively compared using synthetic channel image data
of an eye phantom and a semisynthetic set of retinal channel images
generated by using known transformations. The experiments show that
generalized dual-bootstrap iterative closest point method outperforms
the other evaluated methods in registration accuracy, measured in pixel
error, and the number of successful registrations.


KeywordsFundusimaging, Image registration, Quantitative evaluation, Retinal imaging, Spectral imaging


Last updated on 2018-19-10 at 07:55