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3.12 DWI Denoising
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• Output Data
• Non-local means filter
• Discrete gaussian filter
• References
3.12.1
Input Data
Mandatory Input:
• Diffusion weigthed image
Optional Input:
• Binary mask to define a denoising area.
3.12.2
Output Data
• Denoised DWI: if a mask is set for denoising, all voxel excluding the masked area are set to 0.
3.12.3
Non-local means filter
Denoise the input DWI using a non local means algorithm. For more details refer to [1] and [2].
Parameters:
• Searchradius: defines the size of the neighborhood V (Fig. 1 b)) in which the voxels will be weighted to
reconstruct the center voxel. The resulting neighborhood size is defined as 2x searchradius + 1 (e.g. a
searchradius of 1 generates a neighborhood cube with size 3x3x3).
• Comparisonradius: defines the size of the compared neighborhoods N (Fig. 1 b)) around each voxel. The
resulting neighborhood size is defined as 2x comaprisonradius + 1 (e.g. a comparisonradius of 1 generates
a neighborhood cube with size 3x3x3).
• Noise variance: the variance of the noise need to be set for filtering. An estimation of the noise varinace will
be implemented soon.
• Rician adaption: if checked the non-local means uses an adaption for Rician distributed noise.
• Joint information: if checked the whole DWI is seen as a vector image, weighting each voxels complete vector,
instead of weighting each channel seperate. (This might be a bit faster, but is less accurate)
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