Skip to main content

Advertisement

Log in

Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step.

Methods

In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours.

Results

The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method.

Conclusion

In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Fuller J, Denehy G (2001) Concise dental anatomy and morphology. The University of Lowa press, Ames

    Google Scholar 

  2. Bossard D, Dubos N, Trunde F, Huet A, Coudert JL (2004) 3D Computed-assisted surgery in orthodontic treatment of impacted canines in palatal position. Int Congr Ser 1268: 1203–1208

    Article  Google Scholar 

  3. Pongrdcz F, Bdrdosi Z (2006) Dentition planning with image-based occlusion analysis. Int J CARS 1: 149–156

    Article  Google Scholar 

  4. Cucchiara R, Lamma E, Sansoni T (2004) An image analysis approach for automatically re-orienteering CT images for dental implants. Comput Med Imaging Graph 28: 185–201

    Article  PubMed  Google Scholar 

  5. Jain AK, Chen H (2004) Matching of dental X-ray images for human identification. J Pattern Recognit 37: 1519–1532

    Article  Google Scholar 

  6. Zhou J, Abdel-Mottaleb M (2005) A content-based system for human identification based on bitewing dental X-ray images. J Pattern Recognit 38: 2132–2142

    Article  Google Scholar 

  7. Nomir O, Abdel-Mottaleb M (2005) A system for human identification from X-ray dental radiographs. J Pattern Recognit 38: 1295–1305

    Article  Google Scholar 

  8. Mokhtari M, Laurendeau D (1994) Feature detection on 3D images of dental imprints. In: Proceedings of IEEE workshop on biomedical image analysis, pp 287–296

  9. Paulus D, Wolf M, Meller S, Niemann H (1999) Three dimensional computer vision for tooth restoration. Med Image Anal 3(1): 1–19

    Article  PubMed  CAS  Google Scholar 

  10. Kondo T, Ong SH, Chuah JH (2001) Robust arch detection and tooth segmentation in 3D images of dental plaster models. In: Proceeding of IEEE workshop on medical imaging and augmented reality, pp 241–246

  11. Piotrowski M, Szczepaniak PS (2000) Active contour based segmentation of low-contrast medical images. In: International conference on advances in medical signal and information processing, pp 104–109

  12. Chen H, Jain AK (2004) Tooth contour extraction for matching dental radiographs. In: International conference on pattern recognition (ICPR), pp 522–525

  13. Li S, Fevens T, Krzyzak A, Li S (2006) An automatic variational level set segmentation framework for computer aided dental X-ray analysis in clinical environments. Comput Med Imaging Graph 30: 65–74

    PubMed  Google Scholar 

  14. Li S, Fevens T, Krzyzak A, Li S (2006) Automatic clinical image segmentation using pathological modeling, PCA and SVM. Eng Appl Artif Intell 19: 403–410

    Article  Google Scholar 

  15. Shah S, Abaza A, Ross A, Ammar H (2006) Automatic tooth segmentation using active contour without edges. In: Proc on biometric consortium conference, pp 1–6

  16. Scarfe WC, Farman AG (2006) Clnical application of cone-beam computed tomography in dental practice. J Can Dent Assoc 72: 75–80

    PubMed  Google Scholar 

  17. Ning R, Tang X, Conover D, Yu R (2003) Flat panel detector-based cone beam computed tomography with a circle-plus-two-arcs data acquisition orbit: preliminary phantom study. Med Phys 30(7): 1694–705

    Article  PubMed  Google Scholar 

  18. Hannig C, Krieger E, Dullin C, Merten HA, Attin T, Grabbe E, Heidrich G (2006) Volumetry of human molars with flat panel-based volume CT in vitro. Clin Oral Investig 10(3): 253–257

    Article  PubMed  Google Scholar 

  19. Baba R, Ueda K, Okabe M (2004) Using a flat-panel detector in high resolution cone beam CT for dental imaging. Dentomaxillofacial Radiol 33: 285–290

    Article  CAS  Google Scholar 

  20. Keyhaninejad Sh, Zoroofi RA, Setarehdan SK, Shirani Gh (2006) Automated segmentation of teeth in multislice CT images. In: Proc int conf visual information engineering, pp 339–344

  21. Otsu N (1979) A threshold selection method from gray level histograms. IEEE Trans Syst Man Cyber 9: 62–66

    Article  Google Scholar 

  22. Osher S, Sethian J (1989) Front propagating with curvature dependant algorithms based on Hamilton-Jacobi formulation. Commun Pure Appl Math 42: 577–685

    Article  Google Scholar 

  23. Malladi R, Sethian JA, Vemuri BC (1995) Shape modeling with front propagation: a level set approach. IEEE Trans Pattern Anal Mach Intell 17(2): 158–175

    Article  Google Scholar 

  24. Caselles V, Kimmel R, Sapiro G (1997) Geodesic active contour. Int J Comput Vis 22(1): 61–79

    Article  Google Scholar 

  25. Zhao H-K, Chan TF, Merriman B, Osher S (1996) A variational level set approach to multiphase motion. J Comput Phys 127(1): 179–195

    Article  Google Scholar 

  26. Chan T, Vese L (2001) Active contour without edges. IEEE Trans Image Process 24: 266–277

    Article  Google Scholar 

  27. Vese L, Chan T (2002) A multiphase level set framework for image segmentation using the Mumford and Shah model. Int J Comput Vis 50(3): 271–293

    Article  Google Scholar 

  28. Mumford D, Shah J (1989) Optimal approximation by piecewise smooth function and associated variational. Commun Pure Appl Math 42: 577–685

    Article  Google Scholar 

  29. Strumas N, Antonyshyn O, Yaffe MJ, Mawdsley G, Cooper P (1998) Computed tomography artefacts: an experimental investigation of causative factors. Can J Plast Surg 1: 23–29

    Google Scholar 

  30. Robertson DD, Weiss PJ, Fishman EK et al (1998) Evaluation of CT techniques for reducing artifacts in the presence of metallic orthopedicimplants. J Comput Assist Tomogr 12(2): 236–241

    Article  Google Scholar 

  31. www.mathworks.com

  32. www.medalelectronic.com

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohammad Hosntalab.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hosntalab, M., Aghaeizadeh Zoroofi, R., Abbaspour Tehrani-Fard, A. et al. Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set. Int J CARS 3, 257–265 (2008). https://doi.org/10.1007/s11548-008-0230-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-008-0230-9

Keywords

Navigation