Fuzzy similarity based non local means filter for Rician noise removal

2014 ◽  
Vol 74 (15) ◽  
pp. 5533-5556 ◽  
Author(s):  
Muhammad Sharif ◽  
Ayyaz Hussain ◽  
Muhammad Arfan Jaffar ◽  
Tae-Sun Choi
Keyword(s):  
Noise Removal ◽  
Rician Noise ◽  
Local Means ◽  
Fuzzy Similarity ◽  
Non Local

Rician noise removal from MR images using novel adapted selective non-local means filter

2012 ◽  
Vol 72 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Sultan Zia ◽  
M. Arfan Jaffar ◽  
Anwar M. Mirza ◽  
Tae-Sun Choi
Keyword(s):  
Noise Removal ◽  
Rician Noise ◽  
Mr Images ◽  
Local Means ◽  
Non Local

scholarly journals Brain MR image denoising for Rician noise using pre-smooth non-local means filter

2015 ◽  
Vol 14 (1) ◽  
pp. 2 ◽  
Author(s):  
Jian Yang ◽  
Jingfan Fan ◽  
Danni Ai ◽  
Shoujun Zhou ◽  
Songyuan Tang ◽  
...  
Keyword(s):  
Image Denoising ◽  
Rician Noise ◽  
Mr Image ◽  
Local Means ◽  
Non Local

scholarly journals Mixed-Model Noise Removal in 3D MRI via Rotation-and-Scale Invariant Non-Local Means

2019 ◽  
pp. 33-41
Author(s):  
Xiangyuan Liu ◽  
Quansheng Liu ◽  
Zhongke Wu ◽  
Xingce Wang ◽  
Jose Pozo Sole ◽  
...  
Keyword(s):  
Mixed Model ◽  
Noise Removal ◽  
3D Mri ◽  
Scale Invariant ◽  
Local Means ◽  
Non Local

Region-based non-local means algorithm for noise removal

2011 ◽  
Vol 47 (20) ◽  
pp. 1125 ◽  
Author(s):  
W.L. Zeng ◽  
X.B. Lu
Keyword(s):  
Noise Removal ◽  
Local Means ◽  
Non Local

Natural image noise removal using non local means and hidden Markov models in stationary wavelet transform domain

2017 ◽  
Vol 77 (15) ◽  
pp. 20065-20086 ◽  
Author(s):  
Asem Khmag ◽  
Syed Abdul Rahman Al Haddad ◽  
Ridza Azri Ramlee ◽  
Noraziahtulhidayu Kamarudin ◽  
Fahad Layth Malallah
Keyword(s):  
Wavelet Transform ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Noise Removal ◽  
Natural Image ◽  
Transform Domain ◽  
Stationary Wavelet Transform ◽  
Local Means ◽  
Non Local

Laplacian based non-local means denoising of MR images with Rician noise

2013 ◽  
Vol 31 (9) ◽  
pp. 1599-1610 ◽  
Author(s):  
Hemalata V. Bhujle ◽  
Subhasis Chaudhuri
Keyword(s):  
Rician Noise ◽  
Mr Images ◽  
Local Means ◽  
Non Local

scholarly journals Segmentation of Tumor in MRI Brain Images using Morphological Operators and Non-Local Means Filter

2019 ◽  
Vol 8 (4) ◽  
pp. 10524-10529
Keyword(s):  
Brain Tumor ◽  
Performance Metrics ◽  
Similarity Index ◽  
Clinical Analysis ◽  
Abnormal Development ◽  
Proton Density ◽  
Rician Noise ◽  
Morphological Operators ◽  
Local Means ◽  
Non Local

Brain Tumor is the abnormal development of tissues in the brain. According to survey report Times of India, 2019 around 5, 00,000 people are diagnosed with brain tumor in India. Among 5, 00,000 people 20 percent are children. Magnetic resonance image (MRI) used for clinical analysis of human body are sensitive to redundant Rician noise. Rician is the type of noise added during the acquisition of MRI. The removal of noise variance can be performed by constructing many filters. Among those filters, non-local means filter is used for denoising the Rician noise. In this project simulated MRI data and real time clinical data of T1, T2 and Proton Density weighted MRI images are de-noised and the performance metrics is analyzed using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index Metric). The de-noised image is then subjected to thresholding and morphological operators and the tumor region is segmented.

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