Fast and accurate segmentation of dental x-ray records

  • Authors:

  • Xin Li;Ayman Abaza;Diaa Eldin Nassar;Hany Ammar

  • Affiliations:

  • Lane Dept. of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV;Lane Dept. of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV;Lane Dept. of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV;Lane Dept. of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV

  • Venue:
  • ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
  • Year:
  • 2006

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Abstract

Identification of deceased individuals based on dental characteristics is receiving increased attention. Dental radiographic films of an individual are usually composed into a digital image record. In order to achieve high level of automation in postmortem identification, it is necessary to decompose dental image records into their constituent radiographic films, which are in turn segmented to localize dental regions of interest. In this paper we offer an automatic hierarchical treatment to the problem of cropping dental image records into films. Our approach is heavily based on concepts of mathematical morphology and shape analysis. Among the many challenges we face are non-standard assortments of films into records, variability in record digitization as well as randomness of record background both in intensity and texture. We show by experimental evidence that our approach achieves high accuracy and timeliness.