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Quantification and visualization of alveolar bone resorption from 3D dental CT images

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose A computer aided diagnosis (CAD) system for quantifying and visualizing alveolar bone resorption caused by periodontitis was developed based on three-dimensional (3D) image processing of dental CT images.

Methods The proposed system enables visualization and quantification of resorption of alveolar bone surrounding and between the roots of teeth. It has the following functions: (1) vertical measurement of the depth of resorption surrounding the tooth in 3D images, avoiding physical obstruction; (2) quantification of the amount of resorption in the furcation area; and (3) visualization of quantification results by pseudo-color maps, graphs, and motion pictures. The resorption measurement accuracy in the area surrounding teeth was evaluated by comparing with dentist’s recognition on five real patient CT images, giving average absolute difference of 0.87 mm. An artificial image with mathematical truth was also used for measurement evaluation.

Results The average absolute difference was 0.36 and 0.10 mm for surrounding and furcation areas, respectively. The system provides an intuitive presentation of the measurement results.

Conclusion Computer aided diagnosis of 3D dental CT scans is feasible and the technique is a promising new tool for the quantitative evaluation of periodontal bone loss.

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References

  1. Arai Y, Honda K, Iwai K, Shinoda K (2001) Practical model “3DX” of limited cone-beam X-ray CT for dental use. Proceedings of CARS2001, pp 671–675

  2. Enciso R, Danforth RA, Alexandroni ES, Memon A, Mah J (2006) Third molar evaluation with cone-beam computerized tomography. IJ CARS 1:113–116

    Article  Google Scholar 

  3. Befu S, Tsunashima H, Arai T (2001) A study on three- dimensional image processing method for 3DX multi image micro CT. Proceedings of CARS2001; pp 665–670

  4. Gaggl A, Schultes G, Santler G, Kärcher H (2000) Three- dimensional planning of alveolar ridge distraction by means of distraction implants. Comput Aided Surg 5:35–41

    Article  PubMed  CAS  Google Scholar 

  5. Goulette F, Dutreuil J, Laurgeau C (2002) A new method and a clinical case for computer assisted dental implantology. Proceedings of CARS2002, pp 953–958

  6. Schutyser F, Swennen G, Suetens P (2005) Robust visualization of the dental occlusion by a double scan procedure. MICCAI 2005, LNCS 3749: 368–374

    Google Scholar 

  7. Lamecker H, Zachow S, Wittmers A, Weber B, Hege HC, Elsholtz B, Stiller M (2006) Automatic segmentation of mandibles in low-dose CT-data. IJ CARS 1(Suppl 1):393–395

    Google Scholar 

  8. Hilger KB, Larsen R, Kreiborg S, Krarup S, Darvann TA, Marsh JL (2003) Active shape analysis of mandibular growth. MICCAI 2003, LNCS 2879: 902–909

    Google Scholar 

  9. Gladilin E, Ivanov A, Roginsky V (2004) Generic approach for biomechanical simulation of typical boundary value problems in cranio–maxillofacial surgery planning. MICCAI 2004, LNCS 3217: 380–388

    Google Scholar 

  10. Fitzpatrick JM, Balachandran R, Labadie RF (2004) Bite-block relocation error in image-guided otologic surgery. MICCAI 2004, LNCS 3217: 518–525

    Google Scholar 

  11. Li S, Fevens T, KrzyzȦk A, Jin C, Li S (2005) Toward automatic computer aided dental X-ray analysis using level set method. MICCAI 2005, LNCS 3749: 670–678

    Google Scholar 

  12. Misch KA, Yi ES, Sarment DP (2006) Accuracy of cone beam computed tomography for periodontal defect measurements. J Periodontol 77:1261–1266

    Article  PubMed  Google Scholar 

  13. Carranza FA, Jr (1990) Clinical periodontology, 7th edn. W.B. Saunders, Philadelphia

    Google Scholar 

  14. Easley JR (1967) Methods of determining alveolar osseous form. J Periodontol 38:112–118

    PubMed  CAS  Google Scholar 

  15. Greenberg J, Laster L, Listgarten MA (1976) Transgingival probing as a potential estimator of alveolar bone level. J Periodontol 47:514–517

    PubMed  CAS  Google Scholar 

  16. Ursell MJ (1989) Relationships between alveolar bone levels measured at surgery, estimated by transgingival probing and clinical attachment level measurements. J Clin Periodontol 16:81–86

    Article  PubMed  CAS  Google Scholar 

  17. Haralick RM, Sternberg SR, Zhuang X (1987) Image analysis using mathematical morphology. Trans PAMI 9:532–550

    Google Scholar 

  18. Sedgewick R (1990) Algorithms in C. Addison-Wesley, Massachusetts

  19. Coolidge ED (1937) The thickness of the human periodontal membrane. J Ame Dent Asso 24:1260–1270

    Google Scholar 

  20. Suomi JD, Plumbo J, Barbano JP (1968) A comparative study of radiographs and pocket measurements in periodontal disease evaluation. J Periodontol 39:311–315

    PubMed  CAS  Google Scholar 

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Correspondence to Jiro Nagao.

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Nagao, J., Mori, K., Kitasaka, T. et al. Quantification and visualization of alveolar bone resorption from 3D dental CT images. Int J CARS 2, 43–53 (2007). https://doi.org/10.1007/s11548-007-0075-7

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  • DOI: https://doi.org/10.1007/s11548-007-0075-7

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