Artif Intell Rev (2013) 39:225–235
DOI 10.1007/s10462-011-9268-0
New spatial based MRI image de-noising algorithm
M. A. Balafar
Published online: 14 June 2011
© Springer Science+Business Media B.V. 2011
Abstract Nowadays, fast scan techniques are used to reduce scanning times. These tech-
niques raise scanning noise level in MRI systems. Instead of progress made in image
de-noising, still, it is challenging. A novel edge-preserving neighbourhood filter for image
enhancement is proposed. The main focus of this paper is to propose an adaptive filtering
function to account for the image content while try to preserve edge of image. Proposed
algorithm uses the edges of image to do edge-preserving neighbourhood filtering. Contri-
bution of a sample, in neighbourhood of a pixel, in filtering, depends on the space between
the pixel and the sample. In fact, the sample which there is edge between it and the pixel
don’t contribute in the grey level estimation. Promising experimental results on simulated
and real brain images and comparison with state-of-art de-noising algorithm demonstrate the
potential of proposed algorithm.
Keywords De-noising algorithms · MRI · Brain
1 Introduction
The Medical images almost are stored and represented digitally; and this facilitates diagnosis
(Ping-Lin and Teng 2007). Medical imaging types mostly are as follow: ultrasound images,
X-ray computed tomography, digital mammography, and magnetic resonance image (MRI)
(Tian et al. 2007). Researches commonly use MRI images in medical image processing.
MRI images mostly contain fine and complicated structure. Therefore, de-noising of MRI
images remains a challenging issue and one should choose a trade-off between degree of
de-noising in one side and resolution, degrading of fine structures and acquisition speed in
other side. However, noise and inhomogeneity (Balafar et al. 2010a) are two main factors that
degrade performance and usefulness of other Medical imaging algorithms such as segmen-
tation algorithms (Balafar et al. 2008a,b, 2010b,c,d). Moreover, generally noise degrades
M. A. Balafar (B )
Department of Computer, Faculty of Engineering, Tabriz University, Tabriz, Azerbaijane shargi, Iran
e-mail: balafarila@yahoo.com
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