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Automatic correspondence using the enhanced hexagonal center-based inner search algorithm for point-based dental

T Economopoulos1, P A Asvestas, G K Matsopoulos

  • 1Institute of Communication and Computer Systems, 9 Iroon Polytecneiou str. 15780, Athens, Greece.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
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A new enhanced hexagonal center-based inner search algorithm improves automatic point correspondence for dental registration. This method achieves superior accuracy compared to existing techniques in registering dental images.

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Computational Geometry

Background:

  • Accurate dental registration is crucial for various clinical applications.
  • Existing automatic point correspondence methods face challenges in precision and efficiency.
  • The center-based inner search algorithm provides a foundation for image registration.

Purpose of the Study:

  • To propose an enhanced hexagonal center-based inner search algorithm for improved automatic point correspondence in dental registration.
  • To integrate the modified algorithm into a general registration scheme for affine geometrical transformation.
  • To evaluate the performance and accuracy of the proposed algorithm against established methods.

Main Methods:

  • A modified hexagonal center-based inner search algorithm was developed for point correspondence.

Related Experiment Videos

  • Candidate points were extracted from a reference dental image.
  • Corresponding points were identified in a float image using the proposed algorithm.
  • An affine geometrical transformation was applied for automatic registration.

    • Main Results:

    • The enhanced hexagonal center-based inner search algorithm demonstrated superior performance in automatic point correspondence.
    • Qualitative and quantitative evaluations on 24 dental pairs confirmed higher registration accuracy.
    • The proposed algorithm outperformed a well-known method for automatic correspondence.

    Conclusions:

    • The enhanced hexagonal center-based inner search algorithm offers a significant advancement in automatic dental registration.
    • The algorithm provides improved accuracy and efficiency for point correspondence tasks.
    • This method holds promise for enhancing clinical dental imaging analysis and treatment planning.