<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In this paper, a new filtering method based on neutrosophic set (NS) approach of wiener filter is presented to remove Rician noise from magnetic resonance image. A neutrosophic set, a part of neutrosophy theory, studies the origin, nature and scope of neutralities, as well as their interactions with different ideational spectra. Now, we apply the neutrosophic set into image domain and define some concepts and operators for image denoising. The image is transformed into NS domain, described using three membership sets: True (T), Indeterminacy (I) and False (F). The entropy of the neutrosophic set is defined and employed to measure the indeterminacy. The ω-wiener filtering operation is used on T and F to decrease the set indeterminacy and remove noise. The experiments have conducted on simulated Magnetic Resonance images (MRI) from Brainweb database and clinical MR images corrupted by Rician noise. The results show that the NS wiener filter produces better denoising results in terms of visual perception, qualitative and quantitative measures compared with other denoising methods, such as classical wiener filter, the anisotropic diffusion filter, the total variation minimization scheme and non local means filter.</p></abstract>

In this paper, a new filtering method based on neutrosophic set (NS) approach of wiener filter is presented to remove Rician noise from magnetic resonance image. A neutrosophic set, a part of neutrosophy theory, studies the origin, nature and scope of neutralities, as well as their interactions with different ideational spectra. Now, we apply the neutrosophic set into image domain and define some concepts and operators for image denoising. The image is transformed into NS domain, described using three membership sets: True (T), Indeterminacy (I) and False (F). The entropy of the neutrosophic set is defined and employed to measure the indeterminacy. The ω-wiener filtering operation is used on T and F to decrease the set indeterminacy and remove noise. The experiments have conducted on simulated Magnetic Resonance images (MRI) from Brainweb database and clinical MR images corrupted by Rician noise. The results show that the NS wiener filter produces better denoising results in terms of visual perception, qualitative and quantitative measures compared with other denoising methods, such as classical wiener filter, the anisotropic diffusion filter, the total variation minimization scheme and non local means filter.

A New Neutrosophic Approach of Wiener Filtering for MRI Denoising

Department of Electronics and Communication Engineering, P A College of Engineering and Technology, Pollachi, Tamilnadu 642002, India

Department of Electronics and Communication Engineering, PSG College of Technology, Coimbatore, Tamilnadu 641004, India

School of Science, Technology and Engineering Management, Saint Thomas University, Miami Gardens, Florida 33054, USA

Measurement Science Review

{"article-title":"A New Neutrosophic Approach of Wiener Filtering for MRI Denoising"}

In this paper, a new filtering method based on neutrosophic set (NS) approach of wiener filter is presented to remove Rician noise from magnetic resonance...

A New Neutrosophic Approach of Wiener Filtering for MRI Denoising

Online veröffentlicht: 24. Aug. 2013

Seitenbereich: 177 - 186

DOI: https://doi.org/10.2478/msr-2013-0027

Schlüsselwörter
Denoising, Magnetic Resonance imaging, Neutrosophic Set, Rician distribution, wiener

This content is open access.

A New Neutrosophic Approach of Wiener Filtering for MRI Denoising

Online veröffentlicht: 24. Aug. 2013

Seitenbereich: 177 - 186

DOI: https://doi.org/10.2478/msr-2013-0027

SchlüsselwörterDenoising, Magnetic Resonance imaging, Neutrosophic Set, Rician distribution, wiener

This content is open access.

Schlüsselwörter
Denoising, Magnetic Resonance imaging, Neutrosophic Set, Rician distribution, wiener