Early diagnosis of osteoporosis using radiogrammetry and texture analysis from hand and wrist radiographs in Indian population

被引:39
作者
Areeckal, A. S. [1 ]
Jayasheelan, N. [2 ]
Kamath, J. [2 ]
Zawadynski, S. [3 ]
Kocher, M. [4 ]
David S., S. [1 ]
机构
[1] Natl Inst Technol Karnataka, Dept Elect & Commun Engn, Surathkal, Karnataka, India
[2] Manipal Univ, Dept Orthoped, Kasturba Med Coll, Mangalore, Karnataka, India
[3] HUG, Nucl Med Serv, Geneva, Switzerland
[4] Haute Ecole Ingn & Gest Canton Vaud HEIG VD, Dept Ind Technol, Yverdon, Switzerland
关键词
Distal radius; Metacarpal; Osteoporosis; Radiogrammetry; Texture analysis;
D O I
10.1007/s00198-017-4328-1
中图分类号
R5 [内科学];
学科分类号
100201 [内科学];
摘要
We propose an automated low cost tool for early diagnosis of onset of osteoporosis using cortical radiogrammetry and cancellous texture analysis from hand and wrist radiographs. The trained classifier model gives a good performance accuracy in classifying between healthy and low bone mass subjects. Introduction We propose a low cost automated diagnostic tool for early diagnosis of reduction in bone mass using cortical radiogrammetry and cancellous texture analysis of hand and wrist radiographs. Reduction in bone mass could lead to osteoporosis, a disease observed to be increasingly occurring at a younger age in recent times. Dual X-ray absorptiometry (DXA), currently used in clinical practice, is expensive and available only in urban areas in India. Therefore, there is a need to develop a low cost diagnostic tool in order to facilitate large-scale screening of people for early diagnosis of osteoporosis at primary health centers. Methods Cortical radiogrammetry from third metacarpal bone shaft and cancellous texture analysis from distal radius are used to detect low bone mass. Cortical bone indices and cancellous features using Gray Level Run Length Matrices and Laws' masks are extracted. A neural network classifier is trained using these features to classify healthy subjects and subjects having low bone mass. Results In our pilot study, the proposed segmentation method shows 89.9 and 93.5% accuracy in detecting third metacarpal bone shaft and distal radius ROI, respectively. The trained classifier shows training accuracy of 94.3% and test accuracy of 88.5%. Conclusion An automated diagnostic technique for early diagnosis of onset of osteoporosis is developed using cortical radiogrammetric measurements and cancellous texture analysis of hand and wrist radiographs. The work shows that a combination of cortical and cancellous features improves the diagnostic ability and is a promising low cost tool for early diagnosis of increased risk of osteoporosis.
引用
收藏
页码:665 / 673
页数:9
相关论文
共 14 条
[1]
[Anonymous], 1980, TEXTURED IMAGE SEGME
[2]
Areeckal A. S., 2016, P IEEE INT C SIGN PR, P1
[3]
BARNETT E, 1960, Clin Radiol, V11, P166, DOI 10.1016/S0009-9260(60)80012-8
[4]
Image denoising by sparse 3-D transform-domain collaborative filtering [J].
Dabov, Kostadin ;
Foi, Alessandro ;
Katkovnik, Vladimir ;
Egiazarian, Karen .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2007, 16 (08) :2080-2095
[5]
European guidance for the diagnosis and management of osteoporosis in postmenopausal women [J].
Kanis, J. A. ;
McCloskey, E. V. ;
Johansson, H. ;
Cooper, C. ;
Rizzoli, R. ;
Reginster, J. -Y. .
OSTEOPOROSIS INTERNATIONAL, 2013, 24 (01) :23-57
[6]
Kanis J.A., 2008, WHO Sci. Gr. Assess. osteoprosis Prim. Heal. care Lev, P5
[7]
A Preliminary Study on Discrimination of Osteoporotic Fractured Group from Nonfractured Group using Support Vector Machine [J].
Lee, Sooyeul ;
Lee, Jeong Won ;
Jeong, Ji-Wook ;
Yoo, Done-Sik ;
Kim, Seunghwan .
2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-8, 2008, :474-477
[8]
TOPOGRAPHIC DISTANCE AND WATERSHED LINES [J].
MEYER, F .
SIGNAL PROCESSING, 1994, 38 (01) :113-125
[9]
Pierre Soille, 2004, MORPHOLOGICAL IMAGE
[10]
Estimation of bone mineral density by digital X-ray radiogrammetry:: Theoretical background and clinical testing [J].
Rosholm, A ;
Hyldstrup, L ;
Bæksgaard, L ;
Grunkin, M ;
Thodberg, HH .
OSTEOPOROSIS INTERNATIONAL, 2001, 12 (11) :961-969