【MRtrix】MRtrixを用いた拡散MRIのノイズ除去 ~Denoise~

1. 目的
2. コマンド
2.1. 使用例

1. 目的

  • MRtrixを用いた拡散MRIのノイズ除去(Denoise)

2. コマンド

拡散MRIのノイズ除去には、MRtrixdwidenoiseを用いる。dwidenoiseは、Marchenko-Pastur PCAを用いたデノイズである。




     dMRI noise level estimation and denoising using Marchenko-Pastur PCA


     dwidenoise [ options ] dwi out

        dwi          the input diffusion-weighted image.

        out          the output denoised DWI image.


     DWI data denoising and noise map estimation by exploiting data redundancy
     in the PCA domain using the prior knowledge that the eigenspectrum of
     random covariance matrices is described by the universal Marchenko-Pastur
     (MP) distribution. Fitting the MP distribution to the spectrum of
     patch-wise signal matrices hence provides an estimator of the noise level
     'sigma', as was first shown in Veraart et al. (2016) and later improved in
     Cordero-Grande et al. (2019). This noise level estimate then determines
     the optimal cut-off for PCA denoising.

     Important note: image denoising must be performed as the first step of the
     image processing pipeline. The routine will fail if interpolation or
     smoothing has been applied to the data prior to denoising.

     Note that this function does not correct for non-Gaussian noise biases
     present in magnitude-reconstructed MRI images. If available, including the
     MRI phase data can reduce such non-Gaussian biases, and the command now
     supports complex input data.


  -mask image
     Only process voxels within the specified binary brain mask image.

  -extent window
     Set the patch size of the denoising filter. By default, the command will
     select the smallest isotropic patch size that exceeds the number of DW
     images in the input data, e.g., 5x5x5 for data with <= 125 DWI volumes,
     7x7x7 for data with <= 343 DWI volumes, etc.

  -noise level
     The output noise map, i.e., the estimated noise level 'sigma' in the data.
     Note that on complex input data, this will be the total noise level across
     real and imaginary channels, so a scale factor sqrt(2) applies.

  -datatype float32/float64
     Datatype for the eigenvalue decomposition (single or double precision).
     For complex input data, this will select complex float32 or complex
     float64 datatypes.

  -estimator Exp1/Exp2
     Select the noise level estimator (default = Exp2), either: 
     * Exp1: the original estimator used in Veraart et al. (2016), or 
     * Exp2: the improved estimator introduced in Cordero-Grande et al. (2019).

Standard options

     display information messages.

     do not display information messages or progress status; alternatively,
     this can be achieved by setting the MRTRIX_QUIET environment variable to a
     non-empty string.

     display debugging messages.

     force overwrite of output files (caution: using the same file as input and
     output might cause unexpected behaviour).

  -nthreads number
     use this number of threads in multi-threaded applications (set to 0 to
     disable multi-threading).

  -config key value  (multiple uses permitted)
     temporarily set the value of an MRtrix config file entry.

     display this information page and exit.

     display version information and exit.


dwidenoise <入力画像> <出力画像>

2.1. 使用例


dwidenoise DWI.nii.gz DWI_denoised.nii.gz


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