Difference between revisions of "T1 bias correction using N4"

Latest revision as of 16:32, 28 August 2015

This pipeline uses the N4 algorithm, implemented in the Insight ToolKit, in order to correct for magnetic field bias.

The only required input is the structural T1 image, e.g. -i T1.nii.gz You can simply use the following line to use the pipeline:

perform_bias_field_correction.py -i T1.nii.gz -o output_dir

The following paragraph describes some other optional arguments:

usage: perform_bias_field_correction.py [-h] -i input_img [input_img ...]
                                        [-m input_mask [input_mask ...]]
                                        [-o directory] [--output_pre prefix]
                                        [--output_suf suffix] [-g]

Pipeline to perform a bias field correction on an input image
or a list of input images.

optional arguments:
  -h, --help            show this help message and exit
  -i input_img [input_img ...], --img input_img [input_img ...]
                        Image file or list of input images
  -m input_mask [input_mask ...], --mask input_mask [input_mask ...]
                        Mask image or list of mask images (optional)
  -o directory, --output_dir directory
                        Output directory containing the registration result
                        Default is the current directory
  --output_pre prefix   Output result prefix
  --output_suf suffix   Output result suffix
  -g, --graph           Print a graph describing the node connections

Further information can be found here:

• • [N4 algorithm ITK documentation](http://www.itk.org/Doxygen/html/classitk_1_1N4BiasFieldCorrectionImageFilter.html)
  • [Insight Article](http://hdl.handle.net/10380/3053)
  • [scholar article describing the algorithm](http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=668698&tag=1)