Paper Title
Pre-Processing Techniques For Breast Cancer Detection In Mammography Images
Article Identifiers
Authors
Dr.P.Indra , R.Yoganapriya
Keywords
Mammogram, MIAS dataset, ROI, Median filter, Improved statistical based bilateral filter, MATLAB.
Abstract
Breast cancer is very common and considered as the second dangerous disease all over the world due to its mortality rate. So, if the detection is early enough, it can reduce the death rate. Image processing techniques are applied to accurately segment the Region of Interest (ROI) prior to abnormality detection in digital mammograms. The digital mammograms can majorly classify into two types, normal and abnormal. Abnormal cases are taken for further process. In this paper, some of the Non-linear techniques are applied to the mammogram images for the removal of noise at pre-processing. Noise removal is done by using lee filter, frost filter, median filter and improved statistical based bilateral filter. The best filter is selected by measures of MSE, PSNR and SSIM. Mammogram from MIAS database is taken for simulation.
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How To Cite
"Pre-Processing Techniques For Breast Cancer Detection In Mammography Images", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 7, page no.a79-a83, July-2023, Available :https://ijnrd.org/papers/IJNRD2307012.pdf
Issue
Volume 8 Issue 7, July-2023
Pages : a79-a83
Other Publication Details
Paper Reg. ID: IJNRD_200752
Published Paper Id: IJNRD2307012
Downloads: 000121115
Research Area: Electronics & Communication Engg.Â
Country: Salem, Tamilnadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2307012.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307012
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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