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JACIII Vol.11 No.8 pp. 1049-1058
doi: 10.20965/jaciii.2007.p1049
(2007)

Paper:

Use of Fuzzy Neural Network in Diagnosing Postmenopausal Women with Osteoporosis Based on Dental Panoramic Radiographs

Agus Zainal Arifin*1, Akira Asano*2, Akira Taguchi*3,
Takashi Nakamoto*4, Masahiko Ohtsuka*4, Mikio Tsuda*5,
Yoshiki Kudo*6, and Keiji Tanimoto*4

*1Department of Informatics, Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS), Jurusan Teknik Informatika, Kampus ITS Sukolilo, Surabaya, 60113, Indonesia

*2Division of Information Engineering, Graduate School of Engineering, Hiroshima University, 1-7-1 Kagamiyama, Higashi-Hiroshima 739-8521, Japan

*3Department of Oral and Maxillofacial Radiology, Hiroshima University Hospital, Hiroshima, Japan

*4Department of Oral and Maxillofacial Radiology, Division of Medical Intelligence and Informatics, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan

*5Department of Obstetrics and Gynecology, Mazda Hospital, Hiroshima, Japan

*6 Department of Obstetrics and Gynecology, Division of Clinical Medical Science, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan

Received:
March 15, 2007
Accepted:
June 24, 2007
Published:
October 20, 2007
Keywords:
computer-aided diagnosis, fuzzy neural network, osteoporosis, panoramic radiograph
Abstract

A thin or eroded cortex of the mandible detected on dental panoramic radiographs is independently associated with low skeletal bone mineral density (BMD) or osteoporosis in postmenopausal women. The purposes of this study were to develop new computer-aided diagnosis system that combines these two panoramic measures by using fuzzy neural networks (FNN) for identifying postmenopausal women with osteoporosis. Dental panoramic radiographs of 100 postmenopausal women who visited our clinic and had BMD assessments at the lumbar spine and the femoral neck were used in this study. Mandibular cortical width and shape were measured by computer-aided systems and used as the inputs. This system partitioned the input space into a set of subspaces using a novel fuzzy thresholding and constructed the fuzzy inference system incorporated with multi layer perceptron neural network. Our results show that the combination of cortical width and shape by using FNN can be used for the identification of postmenopausal women with osteoporosis in dental clinic. Dentists may identify postmenopausal women accurately by using the new FNN based system and refer them to medical professional for BMD testing.

Cite this article as:
A. Arifin, A. Asano, A. Taguchi, <. Nakamoto, M. Ohtsuka, M. Tsuda, <. Kudo, and K. Tanimoto, “Use of Fuzzy Neural Network in Diagnosing Postmenopausal Women with Osteoporosis Based on Dental Panoramic Radiographs,” J. Adv. Comput. Intell. Intell. Inform., Vol.11, No.8, pp. 1049-1058, 2007.
Data files:
References
  1. [1] C. Cooper, “Epidemiology of osteoporosis,” Osteoporosis Int., 9, pp. S2-S8, 1999.
  2. [2] M. Iki, S. Kagamimori, Y. Kagawa, T. Matsuzaki, H. Yoneshima, and F. Marumoa, “Bone Mineral Density of the Spine, Hip and Distal Forearm in Representative Samples of the Japanese Female Population: Japanese Population-Based Osteoporosis (JPOS) Study,” Osteoporosis Int., 12, pp. 529-537, 2001.
  3. [3] S. M. Cadarette, S. B. Jaglal, N. Kreiger, W. J. McIsaac, G. A. Darlington, and J. V. Tu, “Development and validation of the Osteoporosis Risk Assessment Instrument to facilitate selection of women for bone densitometry,” CMAJ, 162, pp. 1289-1294, 2000.
  4. [4] T. Shimano, Y. Suzuki, and T. Sasaki, “Long-term trend of dental radiographic examination in Japan: analysis on health insurance data,” Dental Radiology, 42, pp. 9-21, 2002 (in Japanese).
  5. [5] E. Klemetti, S. Kolmakov, and H. Kroger, “Pantomography in assessment of the osteoporosis risk group,” Scandinavian Journal of Dental Research, 102, pp. 68-72, 1994.
  6. [6] A. Taguchi, Y. Suei, M. Ohtsuka, K. Otani, K. Tanimoto, and M. Ohtaki, “Usefulness of panoramic radiography in the diagnosis of postmenopausal osteoporosis in women. Width and morphology of inferior cortex of the mandible,” Dentomaxillofacial Radiology, 25, pp. 263-267, 1996.
  7. [7] A. M. Bollen, A. Taguchi, P. P. Hujoel, and L. G. Hollender, “Casecontrol study on self-reported osteoporotic fractures and mandibular cortical bone,” Oral Surgery Oral Medicine Oral Pathology Oral Radiology & Endodontics, 90, pp. 518-524, 2000.
  8. [8] H. Devlin and K. Horner, “Mandibular radiomorphometric indices in the diagnosis of reduced skeletal bone mineral density,” Osteoporosis Int., 13, pp. 373-378, 2002.
  9. [9] K. Horner, H. Devlin, and L. Harvey, “Detecting patients with low skeletal bone mass,” Journal of Dentistry, 30, pp. 171-175, 2002.
  10. [10] B. Drozdzowska, W. Pluskiewicz, and B. Tarnawska, “Panoramicbased mandibular indices in relation to mandibular bone mineral density and skeletal status assessed by dual energy Xray absorptiometry and quantitative ultrasound,” Dentomaxillofacial Radiology, 31, pp. 361-367, 2002.
  11. [11] R. E. Persson, L. G. Hollender, L. V. Powell, M. I. MacEntee, C. C. Wyatt, H. A. Kiyak, and G. R. Persson, “Assessment of periodontal conditions and systemic disease in older subjects. I. Focus on osteoporosis,” Journal of Clinical Periodontology, 29, pp. 796-802, 2002.
  12. [12] T. Nakamoto, A. Taguchi, M. Ohtsuka, Y. Suei, M. Fujita, K. Tanimoto, M. Tsuda, M. Sanada, K. Ohama, J. Takahashi, and M. Rohlin, “Dental panoramic radiograph as a tool to detect postmenopausal women with low bone mineral density: untrained general dental practitioners’ diagnostic performance,” Osteoporosis Int., 14, pp. 659-664, 2003.
  13. [13] A. Taguchi, M. Sanada, E. Krall, T. Nakamoto, M. Ohtsuka, Y. Suei, K. Tanimoto, I. Kodama, M. Tsuda, and K. Ohama, “Relationship between dental panoramic radiographic findings and biochemical markers of bone turnover,” Journal of Bone and Mineral Research, 18, pp. 1689-94, 2003.
  14. [14] A. Taguchi, Y. Suei, M. Sanada, M. Ohtsuka, T. Nakamoto, H. Sumida, K. Ohama, and K. Tanimoto, “Validation of dental panoramic radiography measures for identifying postmenopausal women with spinal osteoporosis,” American Journal of Roentgenology, 183, pp. 1755-1760, 2004.
  15. [15] A. Halling, G. R. Persson, J. Berglund, O. Johansson, and S. Renvert, “Comparison between the Klemetti index and heel DXA BMD measurements in the diagnosis of reduced skeletal bone mineral density in the elderly,” Osteoporosis Int., 16, pp. 999-1003, 2005.
  16. [16] A. Taguchi, M. Tsuda, M. Ohtsuka, I. Kodama, M. Sanada, T. Nakamoto, K. Inagaki, T. Noguchi, Y. Kudo, Y. Suei, K. Tanimoto, and A. M. Bollen, “Use of dental panoramic radiographs in identifying younger postmenopausal women with osteoporosis,” Osteoporosis Int., 17, pp. 387-394, 2006.
  17. [17] T. Nakamoto, A. Taguchi, A. Asano, M. Ohtsuka, Y. Suei, M. Fujita, M. Sanada, K. Ohama, and K. Tanimoto, “Computer-aided diagnosis of low skeletal bone mass on panoramic radiographs,” Journal of Dental Research, 83, Special issue A, No.1953, 2004.
  18. [18] A. Z. Arifin, A. Asano, A. Taguchi, T. Nakamoto, M. Ohtsuka, M. Tsuda, Y. Kudo, and K. Tanimoto, “Computer-aided system for measuring the mandibular cortical width on dental panoramic radiographs in identifying postmenopausal women with low bone mineral density,” Osteoporosis Int., 17, pp. 753-759, 2006.
  19. [19] A. G. Farman and T. T. Farman, “Extraoral and panoramic systems,” Dental Clinics of North America, 44, pp. 257-272, 2000.
  20. [20] H. Orimo, Y. Hayashi, M. Fukunaga, T. Sone, S. Fujiwara, M. Shiraki, K. Kushida, S. Miyamoto, S. Soen, J. Nishimura, Y. Oh-Hashi, T. Hosoi, I. Gorai, H. Tanaka, T. Igai, and H. Kishimoto, “Osteoporosis Diagnostic Criteria Review Committee: Japanese Society for Bone and Mineral Research 2001 Diagnostic criteria for primary osteoporosis: year 2000 revision,” Journal of Bone and Mineral Metabolism, 19, pp. 331-337, 2001.
  21. [21] S. Fujiwara, N. Masunari, G. Suzuki, and P. D. Ross, “Performance of osteoporosis risk indices in a Japanese population,” Current Therapeutic Research, 62, pp. 586-593, 2001.
  22. [22] A. Z. Arifin, A. Asano, A. Taguchi, T. Nakamoto, M. Ohtsuka, M. Tsuda, Y. Kudo, and K. Tanimoto, “Identification of low bone mineral density based on the mandibular cortex by fuzzy neural network,” Proc. Joint 3rd Int. Conf. on Soft Computing and Intelligent Systems and 7th Int. Symposium on advanced Intelligent Systems, pp. 1860-1865, 2006.
  23. [23] M. Sezgin and B. Sankur, “Survey over image thresholding techniques and quantitative performance evaluation,” Journal of Electronic Imaging, 13, pp. 146-165, 2004.
  24. [24] L. K. Huang and M. J. J. Wang, “Image thresholding by minimizing the measures of fuzziness,” Pattern Recognition, 28, pp. 41-51, 1995.
  25. [25] A. Z. Arifin and A. Asano, “Image segmentation by histogram thresholding using hierarchical cluster analysis,” Pattern Recognition Letters, 27, pp. 1515-1521, 2006.
  26. [26] L. K. Koh, W. B. Sedrine, T. P. Torralba, A. Kung, S. Fujiwara, S. P. Chan, Q. R. Huang, R. Rajatanavin, K. S. Tsai, H.M. Park, and J. Y. Reginster; Osteoporosis Self-Assessment Tool for Asians (OSTA) Research Group 2001, “A simple tool to identify Asian women at increased risk of osteoporosis,” Osteoporosis Int., 12, pp. 699-705, 2001.
  27. [27] F. Richy, M. Gourlay, P. D. Ross, S. S. Sen, L. Radican, F. De Ceulaer, W. Ben Sedrine, O. Ethgen, O. Bruyere, and J. Y. Reginster, “Validation and comparative evaluation of the osteoporosis selfassessment tool (OST) in a Caucasian population from Belgium,” QJM, 97, pp. 39-46, 2004.
  28. [28] R. B. Cook, D. Collins, J. Tucker, and P. Zioupos, “Comparison of questionnaire and quantitative ultrasound techniques as screening tools for DXA,” Osteoporosis Int., 16, pp. 1565-1575, 2005.
  29. [29] A. Z. Arifin, A. Asano, A. Taguchi, T. Nakamoto, M. Ohtsuka, M. Tsuda, Y. Kudo, and K. Tanimoto, “Computer-aided system for measuring the mandibular cortical width on dental panoramic radiographs in identifying postmenopausal women with low bone mineral density,” Osteoporosis Int., 17, pp. 753-759, 2006.

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