Robust retinal image registration using expectation maximisation with mutual information

Reel, Parminder; Dooley, Laurence and Wong, Patrick (2013). Robust retinal image registration using expectation maximisation with mutual information. In: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 26-31 May 2013, Vancouver, Canada, pp. 1118–1122.

Abstract

Retinal images (RI) are widely used to diagnose a variety of eye conditions and diseases such as myopia and diabetic retinopathy. They are inherently characterised by having non-uniform illumination and low-contrast homogeneous regions which represent a unique set of challenges for retinal image registration (RIR). This paper investigates using the expectation maximization for principal component analysis based mutual information (EMPCA-MI) algorithm in RIR. It combines spatial features with mutual information to efficiently achieve improved registration performance. Experimental results for mono-modal RI datasets verify that EMPCA-MI together with Powell-Brent optimization affords superior robustness in comparison with existing RIR methods, including the geometrical features method.

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