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International Journal of Soft Computing
Year: 2009 | Volume: 4 | Issue: 5 | Page No.: 223-228
Texture Analysis of Bone CT Images for Classification and Characterization of Bone Quality
T. Kalpalatha Reddy and N. Kumaravel
 
References
Arivazhagan, S. and L. Ganesan, 2006. Texture classification using wavelet transform. Pattern Recog. Lett., 27: 1875-1883.
CrossRef  |  

Candes, E., L. Demanet, D. Donoho and L. Ying, 2006. Fast discrete curvelet transforms. Multistage Model. Simulat., 5: 861-899.
CrossRef  |  Direct Link  |  

Cendre, E., V. Kaftandjian, G. Peix, M. Joulin, D. Mitton and D. Babot, 2000. An investigation of segmentation methods and texture analysis applied to Tomographic images of human vertebral cancellous bone. J. Microscopy, 197: 305-316.
PubMed  |  Direct Link  |  

Chen, G.Y., T.D. Bui and A. Krzyak, 2005. Rotation invariant pattern recognition using ridgelet, wavelet cycle-spinning and Fourier features. Pattern Recog., 38: 2314-2322.
CrossRef  |  

Donoho, D.L. and M.R. Duncan, 2000. Digital curvelet transform: Strategy, implementation and experiments Proc. SPIE, 4056: 12-30.
Direct Link  |  

Eriksen, E.F., L. Mosekilde and F. Melsen, 1985. Trabecular bone resorption depth decreases with age: Differences between normal males and females. J. Bone, 6: 141-146.
PubMed  |  Direct Link  |  

Fukunaga, K., 1990. Introduction to Statistical Pattern Recognition. 2nd Edn., Academic Press, Orlando, FL., ISBN: 0-12-269851-7.

Hannan, M.T., D.T. Felsen and J.A. Anderson, 1992. Bone mineral density in elderly men and women: Results from the Framingham osteoporosis study. J. Bone Mineral Res., 7: 547-553.
PubMed  |  Direct Link  |  

Haralick, R.M., K. Shanmugam and I.H. Dinstein, 1973. Textural features for image classification. IEEE Trans. Syst. Man Cybern., SMC-3: 610-621.
CrossRef  |  Direct Link  |  

Jakubas, J.P., A. Sawicki and P. Przecolocki, 2003. Assessment of trabecular bone structure in post menopausal and sensile osteoporosis in women by image analysis. Scand. J. Rheumatol., 32: 295-299.

Kornel, P., M. Bela, S. Rainer, D. Zalan, T. Zsolt and F. Janos, 1998. Application of neural network in medicine. Diag. Med. Technol., 4: 538-546.
Direct Link  |  

Krug, R., J.C. Gamito, A. Burgwardt, S. Haase, J.W. Sedat, W.C. Moss and S. Majumdar, 2005. Wavelet based characterization of vertebral trabecular bone structure from MR images of specimen at 3 tesla compared to micro CT measurements. Proceedings of the IEEE 27th Annual Conference onEngineering in Medicine and Biology, Sept. 1-4, Shangai, China, pp: 7040-7043.

Lucia, D. and L. Semlar, 2007. A comparison of wavelet, ridgelet and curvelet-based texture classification algorithms in computed tomography. Comput. Biol. Med., 37: 486-498.
CrossRef  |  Direct Link  |  

Reddy, T.K. and N. Kumaravel, 2009. Assessment of Bone Architecture Using Wavelet Based Multiresolution Texture Analysis. NCISE, USA.

Riggs, B.L., H.W. Wahner and W.L. Dunn, 1981. Differential changes in bone mineral density of the appendicular and axial skeleton with aging relationship to spinal osteoporosis. J. Clin. Invest., 67: 328-335.

Simina, V. and K. Najarian, 2009. A unified method based on wavelet filtering and Active contour models for segmentation of pelvic CT images. Proceedings of the CME International Conference on Complex Medical Engineering, Apr. 9-11, Virginia Commonwealth Univ. Richmond, VA., pp: 1-5.

Southard, T.E. and K.A. Southard, 1996. Detection of simulated osteoporosis in maxillae using radiographic texture analysis. IEEE. Trans. Biomed. Eng., 43: 123-132.
Direct Link  |  

Unser, M., 1986. Local linear transform for texture measurements. Signal Proc., 11: 61-79.
Direct Link  |  

Ying, L., 2005. CurvelLab 2.0. California Institute of Technology, California.

Yongqing, X. and V.R. Yingling, 2006. Comparative assessment of bone mass and structure using texture-based and histomorphometric analysis. J. Bone, 40: 544-552.