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DWT based Feature Extraction for Classification of Untreated MRI Mammogram of Breast Cells and Normal Cells

by Sushma S., Balasubramanian S., Latha K. C.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 157 - Number 8
Year of Publication: 2017
Authors: Sushma S., Balasubramanian S., Latha K. C.
10.5120/ijca2017912797

Sushma S., Balasubramanian S., Latha K. C. . DWT based Feature Extraction for Classification of Untreated MRI Mammogram of Breast Cells and Normal Cells. International Journal of Computer Applications. 157, 8 ( Jan 2017), 37-40. DOI=10.5120/ijca2017912797

@article{ 10.5120/ijca2017912797,
author = { Sushma S., Balasubramanian S., Latha K. C. },
title = { DWT based Feature Extraction for Classification of Untreated MRI Mammogram of Breast Cells and Normal Cells },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 157 },
number = { 8 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume157/number8/26855-2017912797/ },
doi = { 10.5120/ijca2017912797 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:03:25.450302+05:30
%A Sushma S.
%A Balasubramanian S.
%A Latha K. C.
%T DWT based Feature Extraction for Classification of Untreated MRI Mammogram of Breast Cells and Normal Cells
%J International Journal of Computer Applications
%@ 0975-8887
%V 157
%N 8
%P 37-40
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A standout amongst the most effective strategies for bosom malignancy early discovery is mammography. Another strategy for identification and arrangement of miniaturized scale calcifications is displayed. It should be possible in four phases: in the first place, pre processing stage manages clamour expulsion, and standardized the picture. Second stage, K-Means bunching (KMC) is utilized for division and pectoral muscle extraction utilizing territory figuring lastly smaller scale calcifications identification. Third stage comprises of two dimensional discrete wavelet changes are separated from the discovery of miniaturized scale calcifications. And after that, nine measurable components are figured from the LL band of wavelet change.

References
  1. Jernal A, Bray F,Center M M,Ferlay J,Ward E,Forman D.Global cancer statistic.CA cancer J clin.vol 61,2011
  2. http://en.wikipedia.org/wiki/cancer
  3. www.cancerquest.org/breast-cancer-risks.html
  4. Prastawa, M., Bullitt, E., Gerig, G.: ‘Simulation of brain tumors in MRI for evaluation of segmentation efficacy’, Med. Image Anal., 2009, 13, pp. 294–311
  5. Padma, A., Sukanesh, R.: ‘Automatic diagnosis of abnormal tumor region from brain computed tomography images using wavelet based statistical texture features’, Int. J. Comput. Sci., Eng. Inf. Technol. (IJCSEIT), 2011.
  6. E.A. Rashed, I.A. Ismail, S.I. Zaki, Multiresolution mammogram analysis in multilevel decomposition, Pattern Recognition Letters 28, 2007, pp. 286–292.
  7. S. Liu, C.F. Babbs, E.J. Delp, Multiresolution detection of spiculated lesions in digital mammograms, IEEE Transactions on Image Processing 10 (6) , 2001, pp. 874–884.
Index Terms

Computer Science
Information Sciences

Keywords

DWT (Discrete Wavelet Transform) K-nearest neighbor mean standard deviation MRI Mammogram

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