Fractional Brownian Motion Noise Removal in Breast Cancer Magnetic Resonance Images
N. Rajeswaran1, C. Gokilavani2, T. Samraj Lawrence3, P. Ramkumar4

1N. Rajeswaran, Malla Reddy Engineering College (A), Maisammaguda (Telangana), India.
2P. Ramkumar, Malla Reddy Engineering College (A), Maisammaguda (Telangana), India.
3C. Gokilavani, Francis Xavier Engineering College, Tirunelveli (Tamil Nadu), India.
4T. Samraj Lawrence, Francis Xavier Engineering College, Tirunelveli (Tamil Nadu), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 1362-1366 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3476048619/19©BEIESP
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Abstract: In Medical Image Processing, high resolution images are very much essential to analyze the different features of the image for better diagnosis of the disease. Now days, more and more women are getting affected by breast cancer. Magnetic Resonance Imaging is the most popular technique used to diagnose the breast cancer images, whose resolution in turn is affected by the fractional Brownian motion (fBm) noise, Gaussian noise and Salt and Pepper noise. In this paper, wavelet based thresholding techniques namely Visu shrink, SURE shrink and Bayes shrink are implemented to denoise the breast cancer images affected by fBm noise.
Keyword: FBm Noise, Medical Image Processing, Magnetic Resonance Imaging, Wavelet Thresholding.
Scope of the Article: Bioinformatics