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Bone trabecular analysis of proximal femur radiographs for the detection of osteoporosis using anisotropic Morlet wavelet transform
- Source :
- Cluster Computing. 22:14513-14523
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- Osteoporosis is a thinning of the bone that leads to fracture with minimum force. It affects postmenopausal women and elderly of both genders. Bone Mineral Density (BMD) is one of the parameters related to bone strength. For measuring BMD Dual Energy X-ray absorptiometry (DXA) is currently considered as the “gold standard”. Osteoporosis is evaluated in postmenopausal women using low-cost digital hip radiograph in comparison with DXA as a gold standard. (i) To evaluate the morphometry of proximal femur using digital radiograph in the diagnosing osteoporosis in Indian women. (ii) To evaluate the morphometry of metacarpal using digital radiograph in the diagnosing osteoporosis in Indian women. (iii) To calculate the energy at neck, head, and trochanter of the proximal femur using image processing technique of anisotropic Morlet wavelet transform. By using The Anisotropic filter proximal femur is enhanced then the feature is extracted using Morlet wavelet transform. A free medical screening camp for osteoporosis was conducted at SRM Medical College and Research Institute. A total number of 50 (n = 50) Indian women, 18 healthy premenopausal women (n = 18, 36.3 ± 8.7 years) and 32 postmenopausal women (n = 32, 58 ± 9.1 years) whose age ranged from 20 to 85 years were included.
- Subjects :
- musculoskeletal diseases
Orthodontics
Bone mineral
Postmenopausal women
Trochanter
Proximal femur
Computer Networks and Communications
business.industry
Computer science
Radiography
Osteoporosis
020206 networking & telecommunications
02 engineering and technology
Gold standard (test)
medicine.disease
Bone strength
Morlet wavelet
0202 electrical engineering, electronic engineering, information engineering
medicine
020201 artificial intelligence & image processing
business
Software
Subjects
Details
- ISSN :
- 15737543 and 13867857
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- Cluster Computing
- Accession number :
- edsair.doi...........7f28a2b7358fc702d71e2d8b5b39866a
- Full Text :
- https://doi.org/10.1007/s10586-018-2331-8