Zama, Fabiana
(2009)
Denoising and Segmentation of MR Images by Coupled Diffusive Filters.
[Preprint]
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Abstract
The image denoising and segmentation is a fundamental task in many
medical applications based on magnetic resonance image processing.
This problem can be solved by means of nonlinear diffusive filters
requiring the solution of evolutive partial differential equations.
In this work a coupled system of linear and nonlinear
diffusion-reaction equations is proposed and tested for denoising
and segmentation of magnetic resonance images. The discretization of
the coupled system by means of the Finite Element method is
reported. The effectiveness of the model has been tested on MR
images affected by gaussian, impulsive noise and also in the case of
dynamic magnetic resonance images where the data are affected by
noise in the frequency domain.
Abstract
The image denoising and segmentation is a fundamental task in many
medical applications based on magnetic resonance image processing.
This problem can be solved by means of nonlinear diffusive filters
requiring the solution of evolutive partial differential equations.
In this work a coupled system of linear and nonlinear
diffusion-reaction equations is proposed and tested for denoising
and segmentation of magnetic resonance images. The discretization of
the coupled system by means of the Finite Element method is
reported. The effectiveness of the model has been tested on MR
images affected by gaussian, impulsive noise and also in the case of
dynamic magnetic resonance images where the data are affected by
noise in the frequency domain.
Document type
Preprint
Creators
Keywords
Magnetic Resonance Imaging, Nonlinear Diffusive Filtering, Denoising,
Segmentation, Total Variation, Coupled Pde
Subjects
DOI
Deposit date
18 Jun 2009
Last modified
16 May 2011 12:10
URI
Other metadata
Document type
Preprint
Creators
Keywords
Magnetic Resonance Imaging, Nonlinear Diffusive Filtering, Denoising,
Segmentation, Total Variation, Coupled Pde
Subjects
DOI
Deposit date
18 Jun 2009
Last modified
16 May 2011 12:10
URI
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