Preprocessing of Digital Mammogram Image Based on Otsu’s Threshold

Ashgan M. Omer, Mohammed Elfadil

Abstract


Mammograms are difficult images to interpret. Hence, a preprocessing stage is very important to standardize the mammogram image along with the reduction of its size, and improve the quality of image in order to produce reliable image for CAD system. The proposed technique of preprocessing involves removal of unwanted parts from background of the mammogram, removal of pectoral muscle, and image enhancement. Binarization based on Otsu’s threshold is a main process in all preprocessing steps. Multi-level thresholding applied to segment the pectoral muscle, and level three shows perfect results of pectoral muscle segmentation. A propose method applied on 160 images from MIAS database. Using of level-three multi-thresholding technique, the success rate was 96% in mammogram preprocessing stage.       


Keywords


Mammogram; Binarization; Otsu’s Threshold; Multi-level Threshold.

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References


D. N. Ponraj, ME. Jenifer, P. Poongodi, and J. S. Manoharan , “A survey on the preprocessing techniques of mammogram for the detection of breast cancer”, Journal of Emerging Trends in Computing and Information Science, vol. 2, no. 12, pp. 656–664, 2011

A. C. Chaabani, A. Boujelben, A. Mahfoudhi, and M. Abid, “An Automatic Pre-processing Method for Mammographic Images”, International Journal of Digital Content Technology and its Applications, vol.4, no.3, pp. 190-201, 2010

M.Sundaram, K. Ramar, N. Arumugam, and G. Prabin, “Histogram Modified Local Contrast Enhancement for mammogram images”, Applied Soft Computing, vol. 11, no. 8, pp.5809-5816, 2011

Y. Li, H. Chen, Y. Yang, N. Yang, “Pectoral muscle segmentation in mammograms based on homogenous texture and intensity deviation”, Pattern Recognition, vol. 46 , no. 3, pp. 681-691, 2013

S. Dehghani and M. Abbasi, “A Method for Improve Preprocessing Images Mammography”, International Journal of Information and Education Technology, vol.1, no.1, pp. 90-93, 2011

K. S. Camilus, V. K. Govindan, and P. S. Sathidevi, “Pectoral muscle identification in mammograms”, Journal of Applied Clinical Medical Physics, vol. 12, no. 3, pp. 215-230, 2011

I. K. Maitra, S. Naj, S. K. Bandyopadhyay, “Technique for preprocessing of digital mammogram”, Computer Methods and Programs in Medicine, ELSEVIER Journal, vol. 107, pp. 175-188, 2012

WB. Yoon, JE. Oh, EY. Chae, HH. Kim, SY. Lee, KG. Kim, “Automatic detection of pectoral muscle region for computer aided diagnosis using MIAS mammograms”, Biomed Research International, DOI:10.1155/2016/5967580, 2016

MIAS database http://peipa.essex.ac.uk/info/mias.html

N. Chaki, S. H. Shaikh, K. Saeed, “Exploring image binarization techniques”, Studies in computational intelligence , Springer, DOI: 10.1007/978-322-1907-1_2, 2014

C. A. Glasbey, “An analysis of histogram based thresholding algorithms”, Graphical models and image processing, vol. 55, no. 6, pp. 532-537, 1993

N. Otsu, “A threshold selection method from gray-level histogram”, IEEE Trans. Syst. Man Cybern, vol. 9, no. 1, pp. 62-66, 1997

Ch. H. Bindu, K. S. Prasad, “An efficient medical image segmentation using conventional OTSU method”, International Journal of Advanced Science and Technology, vol. 38, pp. 67-74, 2012

S. Arora, J. Acharya, A. Verma, P. K . Panigrahi, “Multilevel thresholding for image segmentation through a fast statistical recursive algorithm”, Pattern Recognition Letters, vol. 29, no. 2, pp. 119-125, 2008

K. Sreedhar and B. Panlal, “Enhancement of Image Using Morphological Transformation”, International Journal of Computer Science & Information Technology (IJCSIT), Vol. 4, No. 1, pp. 33-50, 2012

R. Haralick and L. Shapiro, “Computer and robot vision”, vol. 1, Addison-Wesley Publishing Company, 1992, pp. 174-185

R. D. Yapa and H. Koichi, “A Connected Component Labeling Algorithm for Grayscale Images and Application of the Algorithm on Mammograms”, ACM symposium on Applied Computing, pp. 146-152, 2007

T. S. Huang, G. J. Yang, and G. Y. Tang, “A fast two dimensional median filtering”, IEEE Transaction on Acoustics Speech, and Signal Processing, vol. 27, no. 1, pp. 13-18, 1979

K. Zuiderveld, “Contrast Limited Adaptive Histogram Equalization”, Graphics GemsIV, P Heckbert Ed. Academic Press, 1994, pp. 474-485


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