The Pre-Processing Techniques for Breast Cancer Detection in Mammography Images

Full Text (PDF, 1454KB), PP.47-54

Views: 0 Downloads: 0


R. Ramani 1,* N.Suthanthira Vanitha 2 S. Valarmathy 1

1. Anna University of Technology Coimbatore, TN, India

2. Knowledge institute of technology, Salem, TN, India

* Corresponding author.


Received: 22 Nov. 2012 / Revised: 8 Jan. 2013 / Accepted: 14 Mar. 2013 / Published: 28 Apr. 2013

Index Terms

Mammogram, Pre-processing, Median filter, Adaptive median filter, Mean filters and wiener filter


Presently breast cancer detection is a very important role for worldwide women to save the life. Doctors and radio logistic can miss the abnormality due to inexperience in the field of cancer detection. The pre-processing is the most important step in the mammogram analysis due to poor captured mammogram image quality. Pre-processing is very important to correct and adjust the mammogram image for further study and processing. There are Different types of filtering techniques are available for pre-processing. This filters used to improve image quality, remove the noise, preserves the edges within an image, enhance and smoothen the image. In this paper, we have performed various filters namely, average filter, adaptive median filter, average or mean filter, and wiener filter.

Cite This Paper

R. Ramani,N.Suthanthira Vanitha,S. Valarmathy,"The Pre-Processing Techniques for Breast Cancer Detection in Mammography Images", IJIGSP, vol.5, no.5, pp.47-54, 2013. DOI: 10.5815/ijigsp.2013.05.06


[1]T.C.Wang, N.B. Karayiannis, "Detection of microcalcifications in digital mammograms using wavelets, Medical Imaging," IEEE Transactions, 17, 498 -509, 1998.

[2]R.Mata, E.Nava,F. Sendra, "Microcalcifications detection using multi resolution methods, pattern Recognition,"2000,proceeings,15th International Conference.4,344-347,2000.

[3]X.P.Zhang, "Multiscale tumor detection and segmentation in mammograms," in Proc. IEEE Int. Symp. Biomed. Imag., pp. 213–216, Jul. 2002.

[4]G.Bharatha Sreeja, Dr. P. Rathika, Dr. D. Devaraj'' Detection of Tumours in Digital Mammograms Using Wavelet Based Adaptive Windowing Method''international journal modern education and computer science 2012,3,57-65

[5]S.Saheb Basha, Dr.K.Satya Prasad'' automatic detection of breast cancer mass in Mammograms using morphological operators And fuzzy c –means clustering'' journal of theoretical and applied information technology

[6] ,The American College of Radiology (ACR),

[7]C. C. Boring, T. S. Squires, T. Tong and M. Montgomery, "Cancer Statistics 1994", CA-Cancer J. Clinicians, 44, pp.7-26, 1994. 

[8]H. D. Cheng and Muyi Cu, "Mass Lesion Detection with a Fuzzy Neural Network", J. Pattern Recognition, 37, pp.1189-1200, 2004. 

[9]L..M. Wun, R. M. Merrill, and E. J. Feuer, "Estimating lifetime and age-conditional probabilities of developing cancer," Lifetime Data Anal.,vol. 4, pp. 169–186, 1998.

[10]D. B. Kopans, "The 2009 U.S. preventive services task force guidelines ignore important scientific evidence and should be revised or withdrawn," Radiology, vol. 256, pp. 15–20, 2010.

[11]Muller H, Michoux N, Bandon D, Geissbuhler A. A Review of Content-based Medical Image Retrieval Systems in Medical Application - Clinical Benefits and Future Directions. International Journal of Medical Informatics, 2004, 73(1):1-23.

[12]Smeulders A, Worring M, Santini S, Gupta A, Jain R. Content-Based Image Retrieval at the End of the Early Years. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2000, 22(12):1380-1394.

[13]Peng F, Yuan K, Feng S, Chen W. Pre-processing of CT Brain Images for Content-Based Image Retrieval. In: Proceedings of International Conference on BioMedical Engineering and Informatics, 2008, 208-212.

[14]Cervinka T, Provazník I. Pre-processing for Segmentation of Computer Tomography Images. In: Proceedings of RADIOELEKTRONIKA,2005, 167-170. 

[15]Hussein ZR, Rahmat RW, Nurliyana L, Saripan MI, Dimon MZ. Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images. International Journal of Computer Science and Network Security (IJCSNS),2009, 9 (3): 134-137.

[16]W.Morrow, R.Paranjape, R.Rangayyan, and J.Desautels, 1992. "Regionbased contrastenhancement of mammograms", IEEE Trans. Med. Imag., vol. 11, pp. 392–406.

[17]S.Lai, X.Li W.Bischof, 1989. "On techniques for detecting circumscribed masses in mammograms", IEEE Trans. Med. Imag., vol. 8, pp. 377-386.

[18]Junn shan wen ju,yanhui, guoa, ling zhang, h.d.cheng. automated breast cancer detection and classification using ultrasound images-a survey. Pattern recognition 43,(2010) 299-317

[19]Jwad Nagi Automated Breast Profile Segmentation for ROI Detection Using Digital Mammograms,IEEE EMBS Conference on Biomedical Engineering & Sciences (IECBES 2010), Kuala Lumpur

[20]Maciej A. Mazurowski , Joseph Y. Lo, Brian P. Harrawood, Georgia D. Tourassi, Mutual information-based template matching scheme for detection of breast masses: From mammography to digital breast tomosynthesis, Journal of Biomedical Informatics (2011).

[21]Ratchakit Sakuldee and Somkait Udomhunsakul (2007) 'Objective Performance of Compressed Image Quality Assessments', PWASET, Vol. 26, pp. 434-443. 

[22]Sumathi poobal, g.ravindran,"the performance of fractal image compression on different imaging modalities using objective quality measures," International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462 Vol. 3 No. 1 Jan 2011.