Histogram Based Comparative Analysis of LBP and Improved LBP Based Texture Extraction of Mammogram
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D.Narain Ponraj, Sweety kunjachan, Dr.P.Poongodi, Samuel Manoharan, “A Survey on Texture Analysis of Mammogram for the Detection of Breast Cancer”,CIIT International journal, vol.3, 2011.
American Cancer Society Breast cancer: facts and figures. ACS; 2003–2004.
D.Narain Ponraj, M.Evangelin Jenifer, Dr.P.Poongodi, Samuel Manoharan, “A Survey on the Preprocessing Techniques of Mammogram for the Detection of Breast Cancer.” CIS International journal, vol.2, 2011
Guido M. te Brake and Nico Karssemeijer, “Single and multiscale detection of masses in digital mammograms,” IEEE Transactions on Medical Imaging, vol. 18, No. 7, pp. 628-638, 1999.
L. Van Gool, P. Dewaele and A. Oosterlinck, “Texture analysis” Computer. Vis. Graphics Image Process., pp. 336–357,1985
M. Tuceryan, A.K. Jain, “Texture analysis”, in: C.H. Chen, L.F. Pau, P.S.P. Wang (Eds.), Handbook of Pattern Recognition and Computer Vision, World Scientific Publishing, pp. 235–276, 1993.
A.R. Rao, A Taxonomy for Texture Description and Identification, Springer, Berlin, 1990.
F. Tomita, S. Tsuji, Computer Analysis of Visual Textures, Kluwer Academic, Hingham, MA, 1990.
T.N. Tan, Geometric transform invariant texture analysis, SPIE 2488, pp.475–485, 1995.
R.M. Haralick, “Statistical and structural approaches to Texture,” Proc. IEEE, pp.786–804, 1979.
T.N. Tan, Texture segmentation approaches: a brief review, Proceedings of CIE and IEEE International Conference on Neural Networks and Signal Processing, Guangzhou, China, November 1993.
T.R. Reed, J.M.H. Du Buf, “A review of recent texture segmentation and feature extraction techniques,” CVGIP: Image Understanding pp.359–372, 1993.
L. Van Gool, P. Dewaele, A. Oosterlinck, and Survey: texture analysis anno, pp.336–357, 1983.
Timo Ojala, Matti Pietikainen and David Harwood, “A comparative study of texture measures with classification based on feature distributions”, pattern recognition, vol.29, No.1, 1996,pp-51-59
X. Llado, A. Oliver, J. Freixenet, R. Marti, J. Marti, “A textural approach for mass false positive reduction in mammography”, Computerized Medical Imaging and Graphics 33 pp. 415–422, 2009
B. Manjunath, W. Ma, “ Texture Features for Browsing and Retrieval of Image Data”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18: p. 837-842, 1996.
Ojala T, Pietikainen M, Maenpaa T. “ Multiresolution gray-scale and rotation invariant texture classification with local binary patterns”. IEEE Trans Pattern Anal Machine Intell vol.24, pp.971–87, 2002.
Sahiner B, Chan HP,Wei D, Petrick N, Helvie MA, Adler DD. “Image feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue”. Med Phys vol.23, pp.1671–84,1996.
Qian W, Sun X, Song D, Clark RA. “Digital mammography - wavelet transform and Kalman-filtering neural network in mass segmentation and detection”. Acad Radiol vol.8,pp.1074–82, 2001.
Christoyianni I, Koutras A, Dermatas E, Kokkinakis G. “Computer aided of breast cancer in digitized mammograms”. Comp Med Imag Grap vol.26, pp.309–19, 2002.
Varela C, Tahoces PG, Méndez AJ, Souto M, Vidal JJ. “Computerized detection of breast masses in digitized mammograms”. Comput Biol Med vol.3, pp.214–26,2007.
Ahonen T, Hadid A, Pietikainen M. “ Face detection with local binary patterns: application to face recognition”. IEEE Trans Pattern Anal Machine Intell vol.28, pp.2037–41,2006.
Jun Liu, Xiaoming Liu, Jianxun Chen and J Tang. “ Improved local binary patterns for classification of masses using mammography”. IEEE Trans, 2011.
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