A CASE ON DIGITAL MAMMOGRAM : REVIEW

AMIT KUMAR CHANDANAN

Abstract


In this paper we proposed a method for automatic detection of masses in digital mammogram. The proposed method uses the coding technique achieved good accuracy with Linear Discriminant Analysis (LDA) classification. The classification accuracy by using the coded images is improved much compared to one that obtained from the original image.

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References


Smith, R. A., “Screening women aged 40-49: where are we today?†J Natl Cancer Inst, 1995, pp. 1198-1199.

Tabar, L., Fagerber, G., and Chen, R. H., “Efficacy of breast screening by age: new results from the Swedish two country trialâ€, Cancer, 1995, pp. 1412-1419.

Arodź, T., Kurdziel, M., Sevre, E. O. D., and Yuen, D. A., “Pattern Recognition Techniques for Automatic Detection of Suspicious-looking Anomalies in Mammogramsâ€, Computer Methods and Programs in Biomedicine, Elsevier, 2005, pp. 135-149.

H.D. Cheng, X.J. Shi, R. Min, L.M. Hu, X.P. Cai, H.N. Du (2006) “Approaches for automated detection and classification of masses in mammogramsâ€, Pattern Recognition, Vol. 39, pp. 646-668.

Mavroforakis,M.E.,Georgiou,H.V.,Dimitropoulos, N., Cavouras, D., and Theodoridis, S., “Mammographic masses characterization based on localized texture and dataset fractal analysis using linear, neural and support vector machine classifiersâ€, Artificial Intelligence in Medicine, 2006, pp. 145—162.

Szekely, N, Toth, N. Pataki, B. (2004). A hybrid system for detecting masses in mammographic images. Instrumentation and measurement technology conference, 2004. IMTC 04. Proceeding of the 21st IEEE Vol3, 18-20 May 2004 pp2065-2070.

K. Bovis and S. Singh. Detection of masses in mammograms using texture features. 15th International Conference on Pattern Recognition (ICPR'00), 2:2267, 2000.

Mudigonda, N.R, Rangayyan, R. Desautels, J.E.L (2000); Gradients and texture analysis for the classification of mammographic masses Medical Image, IEEE Transaction on Vol 19, Issue 10, Oct. 2000 pp 1032-1043.

N. Youssry, F.E.Z. Abou-Chadi, and A.M. El-Sayad. Early detection of masses in digitized mammograms using texture features and neuro-fuzzy model. 4th Annual IEEE Conf on Information Technology Applications in Biomedicine, 2003.

Al Mutaz, M. A., Deris, S., Zaki, N. M. 2011. Detection of Masses in Digital Mammogram Using Second Order Statistics and Artificial Neural Network. International Journal of Computer Science & Information Technology (IJCSIT). Vol.3 No.3


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