Cellular Neural Networks and Dynamic Enhancement for Cephalometric Landmarks Detection

  • D. Giordano
  • R. Leonardi
  • F. Maiorana
  • C. Spampinato
Conference paper

DOI: 10.1007/11785231_80

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)
Cite this paper as:
Giordano D., Leonardi R., Maiorana F., Spampinato C. (2006) Cellular Neural Networks and Dynamic Enhancement for Cephalometric Landmarks Detection. In: Rutkowski L., Tadeusiewicz R., Zadeh L.A., Żurada J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science, vol 4029. Springer, Berlin, Heidelberg

Abstract

Cephalometric landmarks detection is a knowledge intensive activity to identify on X-rays of the skull key points to perform measurements needed for medical diagnosis and treatment. We have elsewhere proposed CNNs (Cellular Neural Networks) to achieve an accuracy in automated landmarks detection suitable for clinical practice, and have applied the method for 8 landmarks located on the bone profile. This paper proposes and evaluates a CNNs approach augmented by local image dynamic enhancemet for other 3 landmarks that are notoriously difficult to locate; the advantages of this method in the landmark detection problem are pointed out.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • D. Giordano
    • 1
  • R. Leonardi
    • 2
  • F. Maiorana
    • 1
  • C. Spampinato
    • 1
  1. 1.Dipartimento Ingegneria Informatica e delle TelecomunicazioniUniversity of CataniaCataniaItaly
  2. 2.Policlinico Cittá UniversitariaClinica Odontoiatrica II – University of CataniaCataniaItaly

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