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Enhanced retinal image registration accuracy using expectation maximisation and variable bin-sized mutual information

Reel, P. S.; Dooley, L. S.; Wong, K. C. P. and Börner, A. (2014). Enhanced retinal image registration accuracy using expectation maximisation and variable bin-sized mutual information. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’14), pp. 6682–6686.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1109/ICASSP.2014.6854883
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Abstract

While retinal images (RI) assist in the diagnosis of various eye conditions and diseases such as glaucoma and diabetic retinopathy, their innate features including low contrast homogeneous and nonuniformly illuminated regions, present a particular challenge for retinal image registration (RIR). Recently, the hybrid similarity measure, Expectation Maximization for Principal Component Analysis with Mutual Information (EMPCA-MI) has been proposed for RIR. This paper investigates incorporating various fixed and adaptive bin size selection strategies to estimate the probability distribution in the mutual information (MI) stage of EMPCA-MI, and analyses their corresponding effect upon RIR performance. Experimental results using a clinical mono-modal RI dataset confirms that adaptive bin size selection consistently provides both lower RIR errors and superior robustness compared to the empirically determined fixed bin sizes.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 IEEE
ISBN: 1-4799-2892-5, 978-1-4799-2892-7
Keywords: image registration; ophthalmological image processing; principal component analysis; mutual information; expectation-maximization algorithms
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
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Item ID: 39688
Depositing User: Parminder Reel
Date Deposited: 11 Mar 2014 09:25
Last Modified: 26 May 2018 05:59
URI: http://oro.open.ac.uk/id/eprint/39688
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