WAVELET TRANSFORMATION FOR ENHANCING MAMMOGRAPHIC IMAGES

Authors

  • Ankush Rai School of Computing Science & Engineering, VIT University, Chennai, Tamil Nadu, India
  • Jagadeesh Kannan R School of Computing Science & Engineering, VIT University, Chennai, Tamil Nadu, India

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s1.19739

Keywords:

Digital mammography, wavelet transformation

Abstract

Mammographic images are often prone to noises and consequently make the task of radiologist to come up with the precise diagnosis. Though there are several denoising techniques for the same is available but while denoising they often suffers from the problem of eliminating the micron level details in the noise influenced images. It's a trade-off which prohibits efficient micro-classification of mammary tissues. This, in this study we present a solution for the same by utilizing multi level wavelet transformation to enable preservation of micron level details in the images.  

Downloads

Download data is not yet available.

References

P.Heinlein, J.Drexl, W.Schneider, Integrated Wavelet for enhancement of Microcalcification in Digital mammographyâ€, IEEE Transaction on medical imaging, V.22,n.3, p. 402-413, Mar 2000.

N. Pandey, Z. Salcic, and J. Sivaswamy, Fuzzy logic based microcalcification detectionâ€, Proceedings of the IEEE for Signal Processing Workshop, pp. 662–671, 2000.

R. N. Strickland, H. L. Hahn, Wavelet transforms for detecting microcalcifications in mammogramsâ€, IEEE Trans. Med. Imag., vol. 15, no. 2, pp. 218–229,1996.

M. G. Mini, T. Thomas, A Neural Network Method for Mammogram Analysis Based on Statistical Featuresâ€, Proceedings of TENCON 2003, vol. 4, pp.1489-1492, Oct. 2003

S. Yu, L. Guan, A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram filmsâ€, IEEE Trans. .Med. Imag., vol. 19, no. 2, pp. 115–126, 2000.

Ferreira CBR and Borges DL]: Analysis of mammogram classification using a wavelet transform decomposition. Pattern Recognition Letters 24, 2003, pp973–982.

S.Sentelle, C.Sentelle and MA.Sutton : Multiresolution-Based Segmentation of Calcifications for the Early Detection of Breast Cancer. Real-Time Imaging 8, 2002, pp 237–252.

R.Nakayama, Y.Uchiyama, K.Yamamoto, R.Watanabe, K.Namba, , Computer-aided diagnosis scheme using a filter bank for detection of microcalcification clusters in mammogramsâ€, IEEE Transactions on Biomedical Engineering, vol 53. No.2,p.273-283,Feb 2006.

Paul Bao Lei Zhang,†Noise reduction for magnetic resonance images via adaptive multiscale products thresholdingâ€, IEEE Transactions on Medical Imaging,vol.22,No.9,p.1089-1099,Sep 2003.

M.Sameti, R.K.Ward, J.Morgan-Parkes, B.Palcic, Image Feature Extraction in the Last Screening Mammograms Prior to Detection of Breast Cancer†IEEE Journal of selected topics in signal processing, vol 3,No.1,p.46-52,Feb 2009

C. E. Metz, Some practical issues of experimental design and data analysis in radiological ROC studies,†Invest. Radiol., vol. 24, no. 3, pp. 234–245, Mar. 1989.

Choubey, A.; Sinha, G.R.; Choubey, S., "A hybrid filtering technique in medical image denoising: Blending of neural network and fuzzy inference," Electronics Computer Technology (ICECT), 2011 3rd International Conference on , vol.1, no., pp.170,177, 8-10 April 2011.

doi: 10.1109/ICECTECH.2011.5941584

University of South Florida Digital Mammography, DDSM: Digital Database for Screening Mammography, http://marathon.csee.usf.edu/Mammography/Database.html

Rai, Ankush. "Attribute based Level Adaptive Thresholding Algorithm for Object Extraction." Journal of Advancements in Robotics 1.2 (2015): 64-68.

Rai, Ankush. "A Novel Decomposable Pixel Component Analysis Algorithm for Automating Multispectral Satellite Image Denoising." Research & Reviews: Journal of Embedded System & Applications 2.3 (2015): 18-25.

Rai, Ankush. "High Performance Computing: A Reality at Central-India." International Journal of Innovative Research and Development, ISSN 2278–0211 2.3 (2013): 734-743.

Published

01-04-2017

How to Cite

Rai, A., and J. K. R. “WAVELET TRANSFORMATION FOR ENHANCING MAMMOGRAPHIC IMAGES”. Asian Journal of Pharmaceutical and Clinical Research, vol. 10, no. 13, Apr. 2017, pp. 288-91, doi:10.22159/ajpcr.2017.v10s1.19739.

Issue

Section

Original Article(s)

Most read articles by the same author(s)

<< < 1 2 3 4 > >>