Peer Reviewed

1

DOI

10.17077/omia.1006

Conference Location

Boston, MA, USA

Publication Date

September 2014

Abstract

This paper presents a method to automatically assess the accuracy of image registration. It is applicable to images in which vessels are the main landmarks such as fundus images and angiography. The method simultaneously exploits not only the position, but also the intensity profile across the vasculatures. The accuracy measure is defined as the energy of the odd component of the 1D vessel profile in the difference image divided by the total energy of the corresponding vessels in the constituting images. Scale and orientation-selective quadrature filter banks have been employed to analyze the 1D signal profiles. Subsequently, the relative energy measure has been calibrated such that the measure translates to a spatial misalignment in pixels. The method was validated on a fundus image dataset from a diabetic retinopathy screening program at the Rotterdam Eye Hospital. An evaluation showed that the proposed measure assesses the registration accuracy with a bias of -0.1 pixels and a precision (standard deviation) of 0.9 pixels. The small Fourier footprint of the orientation selective quadrature filters makes the method robust against noise.

Rights

Copyright © 2014, Kedir M. Adal, Rosalie Couvert, D.W. J. Meijer, Jose P. Martinez, Koenraad A. Vermeer, and L.J. van Vliet.

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Ophthalmology Commons

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Sep 14th, 12:00 AM Sep 14th, 12:00 AM

A quadrature filter approach for registration accuracy assessment of fundus images

Boston, MA, USA

This paper presents a method to automatically assess the accuracy of image registration. It is applicable to images in which vessels are the main landmarks such as fundus images and angiography. The method simultaneously exploits not only the position, but also the intensity profile across the vasculatures. The accuracy measure is defined as the energy of the odd component of the 1D vessel profile in the difference image divided by the total energy of the corresponding vessels in the constituting images. Scale and orientation-selective quadrature filter banks have been employed to analyze the 1D signal profiles. Subsequently, the relative energy measure has been calibrated such that the measure translates to a spatial misalignment in pixels. The method was validated on a fundus image dataset from a diabetic retinopathy screening program at the Rotterdam Eye Hospital. An evaluation showed that the proposed measure assesses the registration accuracy with a bias of -0.1 pixels and a precision (standard deviation) of 0.9 pixels. The small Fourier footprint of the orientation selective quadrature filters makes the method robust against noise.