• Anubha
• Dr. AMANDEEP KAUR

MRI images are very useful source of information for the doctors to diagnose the symptoms. Due to the presence of noise in images hides the important information. Hence we need to preserve the quality of image which can be done by removing the noise. Hence denoising is very necessary to get precise images to simplify the accurate observations. For the estimation of noise-free pixels, FSNLM (Fuzzy Similarity based Non-Local Means) filter is used to select homogeneous pixels. In MRI images, Rician noise is present which introduces bias which further corrupts MRI images. The bias correction has been suggested for the removal of bias which increases PSNR and contrast. The Suggested scheme has been tested on simulated data sets and compared with existing method.

dB, FSNLM, IEF, MAE, MRI, NLM, PD, PSNR, SBD, SSIM

"Denoising MRI Images using FSNLM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.501-507, June 2019, Available :http://www.jetir.org/papers/JETIR1907K78.pdf

"Denoising MRI Images using FSNLM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp501-507, June 2019, Available at : http://www.jetir.org/papers/JETIR1907K78.pdf