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An Enhanced Approach for Preprocessing of Mammogram Images using Inverse Daubechies Wavelet Transform and Non-Linear Diffusion

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
S. Kowsalya, D. Shanmuga Priyaa

S Kowsalya and Shanmuga D Priyaa. Article: An Enhanced Approach for Preprocessing of Mammogram Images using Inverse Daubechies Wavelet Transform and Non-Linear Diffusion. International Journal of Computer Applications 130(5):6-12, November 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {S. Kowsalya and D. Shanmuga Priyaa},
	title = {Article: An Enhanced Approach for Preprocessing of Mammogram Images using Inverse Daubechies Wavelet Transform and Non-Linear Diffusion},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {130},
	number = {5},
	pages = {6-12},
	month = {November},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Breast cancer is the most leading cause of death in women nowadays. Screening mammography is currently the best available radiological technique for early detection of breast cancer. The detection of breast cancer is disturbed due to the existence of artifacts which reduce the rate of accuracy. For this reason, the pre-processing of mammogram images is very important in the process of breast cancer analysis because it reduces the number of false positives. This paper discusses about two existing filtering techniques and compares it with the results of a proposed filtering method. It is used to solve the noise removal problems and separate the background region from the breast profile region using an automatic thresholding technique. The results are evaluated on the pre-processing method on a set of images obtained from MIAS database. Thus this preparation phase improves the image quality and accentuates the CAD results more accurately.


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Breast Cancer Detection, Mammogram images, pre-processing, image de-noising, filtering, breast contour detection, pectoral muscle extraction, Inverse Daubechies wavelet transform, non-linear diffusion.