Analysis of texture patterns in diagnosing osteoporosis using proximal femur x-ray images

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Abstract

Low bone mass pathology otherwise called osteoporosis assessed by BMD quantification. DXA is still referred as, gold standard for BMD assessment. Authenticity of BMD, measured by DXA at anatomic sites such as proximal and spine has incorporated WHO initiation in proposing a tool for diagnosing osteoporosis. In India, osteoporosis is widely evident in post-menopausal women and elder members of both the genders. A direct proportionality exists between degree of mortality and morbidity with hip and spine pathology. Foresight in predicting the risk of fracture is an important physician's goal. Though DXA has been considered as the gold standard for BMD measurement (g/cm2), the main loophole is the fact that it won't take in to consideration, bone geometry and its micro architecture. The main objective of the present study was to check roughness potential and trabecular bone wavier-ness of the proximal femur that has been sensed by digital x-ray images in post-menopausal osteoporosis evaluation, when DXA has been used as a gold reference for BMD measurement. DXA BMD of the right proximal femur of 26 (n=26, mean ± SD, age = 53.27 ± 14.6 years) south Indian women aged above 25 years was measured. Protocol devised by WHO was adopted in all women. Digital radiograph of right proximal femur was acquired, confirming to medical technicalities. Different methods were used to carry out texture analysis. Relation of BMD with BMI was justified by the results obtained in this study. The present study deciphered the fact that 23% and 27% were affected by osteoporosis and osteopenia respectively. Osteoporotic women exhibited the higher degree of mean roughness, RMS of roughness, mean wavier value and RMS of wavier of neck region compared to normal women as 17%, 15%, 16% and 16% respectively. © 2011 Springer-Verlag.

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APA

Sapthagirivasan, V., & Anburajan, M. (2011). Analysis of texture patterns in diagnosing osteoporosis using proximal femur x-ray images. In Communications in Computer and Information Science (Vol. 205 CCIS, pp. 383–392). https://doi.org/10.1007/978-3-642-24055-3_39

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