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Automatic Correspondence Methods towards Point-Based Medical Image Registration: An Evaluation Study
Abstract
The accurate estimation of point correspondences is often required in a wide variety of medical image processing applications including image registration. Numerous point correspondence methods have been proposed, each exhibiting its own characteristics, strengths and weaknesses. This chapter presents a comparative study of four automatic point correspondence methods. The four featured methods are the Automatic Extraction of Corresponding Points approach, the Trimmed Iterated Closest Points scheme, the Correspondence by Sensitivity to Movement technique and the Self-Organizing Maps network. All methods are presented, mainly focusing on their distinct characteristics. An extensive set of dental images, subject to unknown transformations, was employed for the qualitative and quantitative evaluation of the four methods, which was performed in terms of registration accuracy. After assessing all methods, it was deduced that the Self-Organizing Maps approach outperformed in most cases the other three methods in comparison.
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