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Automatic correspondence using the enhanced hexagonal centre-based inner search algorithm for point-based dental image registration

¹ Institute of Communication and Computer Systems, 9 Iroon Polytechneiou Str., Athens, Greece; ² Department of Oral and Maxillofacial Radiology, Faculty of Odontology, The Sahlgrenska Academy at Göteborg University, Sweden

*Correspondence to: George K Matsopoulos, 9 Iroon Polytechniou Str., Zografos, 15780, Athens, Greece. E-mail: gmatso{at}esd.ece.ntua.gr

Received 19 April 2007; revised 27 July 2007; accepted 27 July 2007

Objectives: In this paper, the enhanced hexagonal centre-based inner search (EHCBIS) algorithm, for automatic point correspondence, is proposed for dental image registration.

Methods: The presented algorithm is incorporated within a general registration scheme, which is based on extracting a set of candidate points on the reference image, finding their corresponding points in the image to be transformed (float image) using the proposed algorithm and applying a suitable geometrical transformation towards automatic registration. The performance of the proposed algorithm is evaluated against three well-known methods for automatic correspondence, the self-organizing maps, the automatic extraction of corresponding points and the trimmed iterative closest point method, in terms of registration accuracy.

Results: Qualitative and quantitative results on registering 123 dental pairs show that the proposed algorithm outperforms the other methods for automatic correspondence with or without the presence of noise.

Conclusions: The EHCBIS method is capable of defining automatically corresponding points in dental image pairs. It can be incorporated within a general scheme for point-based registration of dental radiographs acquired with or without rigorous a priori standardization. The applied projective transformation provides a reliable model for registering intraoral radiographs. The methodology does not require any segmentation prior to alignment providing subtraction radiographs and fused images for clinical evaluation regarding the evolution of a disease or the response to a therapeutic scheme.

Keywords: dental imaging; registration; automatic point extraction; automatic correspondence