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2016 | OriginalPaper | Chapter

Assessment of Bone Mineral Health of Humans Based on X-Ray Images Using Inference

Authors : Geetha Ganapathi, N. Venkatesh Kumar

Published in: Digital Connectivity – Social Impact

Publisher: Springer Nature Singapore

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Abstract

Bones that provide the structural support of the body, are composed of many inorganic compounds and organic materials that all together can be used to determine the mineral density of the bone. The bone mineral density (BMD) is an index measure that is widely used as an indicator of the health of the bone. A densitometry study from dual X-ray absorptiometry (DEXA) system is a popularly used method to assess BMD. BMD values vary depending on race, age, gender and other health conditions. As DEXA is quite an expensive method and requires frequent calibration process to work properly, in this paper, we explore the possibility of developing an affordable and reliable system depending on single X-ray absorptiometry with the use of supervised learning methods. The methodology based on inference is tested on a data set consisting of spine and pelvis X-ray images of patients of varying ages between 10 and 90 years of PSG Hospitals, Coimbatore, India and the results proved to be an indicator of density of the bone.

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Literature
1.
Abidi, B., Mitckes, M., Abidi, M., Liang, J.: Grayscale enhancement techniques of x-ray images of carry-on luggage. In: Proceedings of SPIE 6th International Conference on Quality Control by Artificial Vision, vol. 5132, pp. 579–591 (2003)
2.
3.
Chappard, D., Chennebault, A., Moreau, M., Legrand, E., Audran, M., Basle, M.F.: Texture analysis of x-ray radiographs is a more reliable descriptor of bone loss than mineral content in a Rat model of localized disuse induced by the Clostridium botulinum toxin. Bone 28(1), 72–79 (2001)CrossRefMATH
4.
Chappard, D., Guggenbuhl, P., Legrand, E., Basle, M.F., Audran, M.: Texture analysis of x-ray radiographs is correlated with bone histomorphometry. J. Bone Miner. Metab. 23, 24–29 (2005)CrossRef
5.
Chen, T., He, T.: xgboost: eXtreme Gradient Boosting. R package version 0.4-2 (2015)
6.
Freund, Y., Schapire, R.: A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 55, 119–139 (1997)MathSciNetCrossRefMATH
7.
8.
9.
Guggenbuhl, P., Bodic, F., Hamel, L., Basle, M.F., Chappard, D.: Texture analysis of x-ray radiographs of iliac bone is correlated with bone micro-CT. Osteoporos. Int. 17, 447–454 (2006)CrossRef
10.
Haralick, R.M., Shanmugam, K., Dinstein, I.H.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. 6, 610–621 (1973)CrossRef
11.
Jimenez-Mendoza, D., Espinosa-Arbelaez, D.G., Giraldo-Betancur, A.L., Hernandez-Urbiola, M.I., Vargas-vazquez, D., Mario, E.: Single x-ray transmission system for bone mineral density determination. Rev. Sci. Instrum. 82, 125105 (2011)CrossRef
12.
Luo, G., Kinney, J.H., Kaufman, J.J., Haupt, D., Chiabrera, A., Siffert, R.S.: Relationship between plain radiographic patterns and three-dimensional trabecular architecture in the human calcaneus. Osteoporos. Int. 9, 339–345 (1999)CrossRef
13.
Materka A., Strzlecki M.: Texture analysis methods a review. COST B11 report, Institute of Electronics, Technical University of Lodz, Brussels (1998)
14.
15.
16.
Ross, Q.J.: Bagging, boosting, and C4. 5. In: AAAI/IAAI, vol. 1 (1996)
17.
18.
19.
Veenland J.F.: Texture analysis of the radiographic trabecular bone pattern in osteoporosis. Ph.D. thesis, Reasmus University, Rotterdam (1999). ISBN 90-75655-04-5
20.
Freund, Y., Scaphire, R.E.: Experiments with a new boosting algorithm. In: Proceedings of 13th International Conference in Machine Learning, pp. 148–156 (1996)
Metadata
Title
Assessment of Bone Mineral Health of Humans Based on X-Ray Images Using Inference
Authors
Geetha Ganapathi
N. Venkatesh Kumar
Copyright Year
2016
Publisher
Springer Nature Singapore
Book
Digital Connectivity – Social Impact

Print ISBN: 978-981-10-3273-8

Electronic ISBN: 978-981-10-3274-5

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-981-10-3274-5_23

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