Pre-Processing Techniques For Breast Cancer Detection In Mammography Images

Registration ID: IJNRD_200752

Published ID: IJNRD2307012

DOI: Click Here to Get

Dr.P.Indra , R.Yoganapriya

Mammogram, MIAS dataset, ROI, Median filter, Improved statistical based bilateral filter, MATLAB.

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.

Published Paper   E-Certificate

Dr.P.Indra & R.Yoganapriya (July-2023). Pre-Processing Techniques For Breast Cancer Detection In Mammography Images. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), a79-a83. https://ijnrd.org/papers/IJNRD2307012.pdf

Volume 8 Issue 7, July-2023

Pages : a79-a83

Paper Reg. ID: IJNRD_200752

Published Paper Id: IJNRD2307012

Downloads: 000121986

Research Area: Electronics & Communication Engg. 

Country: Salem, Tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2307012.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307012

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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