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3.2.8 Automatic Noise Computation

<automatic_noise_computation></automatic_noise_computation>

  • on
  • off

The inherent noise in the DW images is an important property that can drive the registration into local minima. Therefore, the mean and the standard deviation of the noise in both the b0 image and the structural image have to be known by the program.

DIFF_PREP extracts the brain and pads noise into the blank regions resulting from the transformations applied to the original image.

This setting is to tell the program to compute the noise information from the images automatically and use those values instead of the ones in the data properties file.

Because the sole purpose of this noise computation is to pad the non-brain regions, it is more important to extract the structural noise information just outside the brain (which might occur due to parallel imaging) instead of the white noise from the background. Therefore, the algorithm first finds the brain and then samples pixels from a "halo" just outside of the brain and computes the noise information based on these pixels.

Note: If this setting is turned on, the noise values in the data description file will NOT be used. If the tag is set to off, the noise values in the data properties file will be used so they must be entered correctly. These values can be roughly approximated by drawing an ROI in the background of your images, in an area free of ghosting and other artifacts, and measuring the mean and standard deviation within your ROI, using the image processing software of your choice.