File: dwibiascorrect

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mrtrix3 3.0.8-1
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#!/usr/bin/python3

# Copyright (c) 2008-2025 the MRtrix3 contributors.
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
#
# Covered Software is provided under this License on an "as is"
# basis, without warranty of any kind, either expressed, implied, or
# statutory, including, without limitation, warranties that the
# Covered Software is free of defects, merchantable, fit for a
# particular purpose or non-infringing.
# See the Mozilla Public License v. 2.0 for more details.
#
# For more details, see http://www.mrtrix.org/.

# Script that performs B1 field inhomogeneity correction for a DWI volume series
# Bias field is typically estimated using the mean b=0 image, and subsequently used to correct all volumes


def usage(cmdline): #pylint: disable=unused-variable
  from mrtrix3 import algorithm, app #pylint: disable=no-name-in-module, import-outside-toplevel
  cmdline.set_author('Robert E. Smith (robert.smith@florey.edu.au)')
  cmdline.set_synopsis('Perform B1 field inhomogeneity correction for a DWI volume series')
  common_options = cmdline.add_argument_group('Options common to all dwibiascorrect algorithms')
  common_options.add_argument('-mask', metavar='image', help='Manually provide a mask image for bias field estimation')
  common_options.add_argument('-bias', metavar='image', help='Output the estimated bias field')
  app.add_dwgrad_import_options(cmdline)

  # Import the command-line settings for all algorithms found in the relevant directory
  algorithm.usage(cmdline)



def execute(): #pylint: disable=unused-variable
  from mrtrix3 import MRtrixError #pylint: disable=no-name-in-module, import-outside-toplevel
  from mrtrix3 import algorithm, app, image, path, run #pylint: disable=no-name-in-module, import-outside-toplevel

  # Find out which algorithm the user has requested
  alg = algorithm.get_module(app.ARGS.algorithm)

  app.check_output_path(app.ARGS.output)
  app.check_output_path(app.ARGS.bias)
  alg.check_output_paths()

  app.make_scratch_dir()

  grad_import_option = app.read_dwgrad_import_options()
  run.command('mrconvert ' + path.from_user(app.ARGS.input) + ' ' + path.to_scratch('in.mif') + grad_import_option)
  if app.ARGS.mask:
    run.command('mrconvert ' + path.from_user(app.ARGS.mask) + ' ' + path.to_scratch('mask.mif') + ' -datatype bit')

  alg.get_inputs()

  app.goto_scratch_dir()

  # Make sure it's actually a DWI that's been passed
  dwi_header = image.Header('in.mif')
  if len(dwi_header.size()) != 4:
    raise MRtrixError('Input image must be a 4D image')
  if 'dw_scheme' not in dwi_header.keyval():
    raise MRtrixError('No valid DW gradient scheme provided or present in image header')
  if len(dwi_header.keyval()['dw_scheme']) != dwi_header.size()[3]:
    raise MRtrixError('DW gradient scheme contains different number of entries (' + str(len(dwi_header.keyval()['dw_scheme'])) + ' to number of volumes in DWIs (' + dwi_header.size()[3] + ')')

  # Generate a brain mask if required, or check the mask if provided by the user
  if app.ARGS.mask:
    if not image.match('in.mif', 'mask.mif', up_to_dim=3):
      raise MRtrixError('Provided mask image does not match input DWI')
  else:
    run.command('dwi2mask in.mif mask.mif')

  # From here, the script splits depending on what estimation algorithm is being used
  alg.execute()





# Execute the script
import mrtrix3
mrtrix3.execute() #pylint: disable=no-member