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BMC Medical Imaging

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Open Access 01-12-2012 | Research article

Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system

Authors: M S Kavitha, Akira Asano, Akira Taguchi, Takio Kurita, Mitsuhiro Sanada

Published in: BMC Medical Imaging | Issue 1/2012

Abstract

Background

Early diagnosis of osteoporosis can potentially decrease the risk of fractures and improve the quality of life. Detection of thin inferior cortices of the mandible on dental panoramic radiographs could be useful for identifying postmenopausal women with low bone mineral density (BMD) or osteoporosis. The aim of our study was to assess the diagnostic efficacy of using kernel-based support vector machine (SVM) learning regarding the cortical width of the mandible on dental panoramic radiographs to identify postmenopausal women with low BMD.

Methods

We employed our newly adopted SVM method for continuous measurement of the cortical width of the mandible on dental panoramic radiographs to identify women with low BMD or osteoporosis. The original X-ray image was enhanced, cortical boundaries were determined, distances among the upper and lower boundaries were evaluated and discrimination was performed by a radial basis function. We evaluated the diagnostic efficacy of this newly developed method for identifying women with low BMD (BMD T-score of -1.0 or less) at the lumbar spine and femoral neck in 100 postmenopausal women (≥50 years old) with no previous diagnosis of osteoporosis. Sixty women were used for system training, and 40 were used in testing.

Results

The sensitivity and specificity using RBF kernel-SVM method for identifying women with low BMD were 90.9% [95% confidence interval (CI), 85.3-96.5] and 83.8% (95% CI, 76.6-91.0), respectively at the lumbar spine and 90.0% (95% CI, 84.1-95.9) and 69.1% (95% CI, 60.1-78.6), respectively at the femoral neck. The sensitivity and specificity for identifying women with low BMD at either the lumbar spine or femoral neck were 90.6% (95% CI, 92.0-100) and 80.9% (95% CI, 71.0-86.9), respectively.

Conclusion

Our results suggest that the newly developed system with the SVM method would be useful for identifying postmenopausal women with low skeletal BMD.

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The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2342/12/1/prepub

Title: Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
Authors: M S Kavitha
Akira Asano
Akira Taguchi
Takio Kurita
Mitsuhiro Sanada
Publication date: 01-12-2012
Publisher: BioMed Central
Published in: BMC Medical Imaging / Issue 1/2012
Electronic ISSN: 1471-2342
DOI: https://doi.org/10.1186/1471-2342-12-1

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Springer Medicine

Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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