dicom2nifti.py

"""
Import modules
"""

import os                                    # system functions
import nipype.interfaces.freesurfer as fs    # freesurfer
import nipype.interfaces.utility as util     # utility
import nipype.pipeline.engine as pe          # pypeline engine

 
"""
Define experiment specific parameters
"""

#Specification of the folder where the dicom-files are located at
experiment_dir = '~SOMEPATH/experiment'

#Specification of a list containing the identifier of each subject
subjects_list = ['subject1','subject2','subject3']
  
#Specification of the name of the dicom and output folder 
dicom_dir_name = 'dicom' #if the path to the dicoms is: '~SOMEPATH/experiment/dicom'
data_dir_name = 'data'   #if the path to the data should be: '~SOMEPATH/experiment/data'


"""
Define nodes to use
"""

#Node: Infosource - we use IdentityInterface to create our own node, to specify
#                   the list of subjects the pipeline should be executed on
infosource = pe.Node(interface=util.IdentityInterface(fields=['subject_id']),
                                                      name="infosource")
infosource.iterables = ('subject_id', subjects_list)

#Node: DICOMConvert - converts the .dcm files into .nii and moves them into
#                     the folder "data" with a subject specific subfolder
dicom2nifti = pe.Node(interface=fs.DICOMConvert(), name="dicom2nifti")
dicom2nifti.inputs.base_output_dir = experiment_dir + '/' + data_dir_name
#This will store the output to '~SOMEPATH/experiment/data'
dicom2nifti.inputs.file_mapping = [('nifti','*.nii'),('info','dicom.txt'),('dti','*dti.bv*')]
dicom2nifti.inputs.out_type = 'nii'
dicom2nifti.inputs.subject_dir_template = '%s'

#Node ParseDICOMDIR - for creating a nicer nifti overview textfile
dcminfo = pe.Node(interface=fs.ParseDICOMDir(), name="dcminfo")
dcminfo.inputs.sortbyrun = True
dcminfo.inputs.summarize = True
dcminfo.inputs.dicom_info_file = 'nifti_overview.txt'


"""
Define pipeline
"""

#Initiation of the preparation pipeline
prepareflow = pe.Workflow(name="prepareflow")
  
#Define where the workingdir of the all_consuming_workflow should be stored at
prepareflow.base_dir = experiment_dir + '/workingdir_prepareflow'


"""
Specify node connections
"""

#Define pathfinder function
def pathfinder(subject, foldername):
    import os
    experiment_dir = '~SOMEPATH/experiment'
    return os.path.join(experiment_dir, foldername, subject)

#Connect all components
prepareflow.connect([(infosource, dicom2nifti,[('subject_id', 'subject_id')]),
                     (infosource, dicom2nifti,[(('subject_id', pathfinder, dicom_dir_name),
                                                 'dicom_dir')]),
                     (infosource, dcminfo,[(('subject_id', pathfinder, dicom_dir_name),
                                             'dicom_dir')]),
                     ])
  

"""
Run pipeline and create graph
"""

prepareflow.run(plugin='MultiProc', plugin_args={'n_procs' : 2})
prepareflow.write_graph(graph2use='flat')


"""
Clean up (optional)
"""

#to run the loop for each subject
for subject in subjects_list:

    #specify where the nifti_overview.txt file is stored at
    from_path = os.path.join(prepareflow.base_dir,prepareflow.name,'_subject_id_%s'%subject,
                             dcminfo.name,dcminfo.inputs.dicom_info_file)

    #specify where to store the nifti_overview.txt file at
    to_path = os.path.join(dicom2nifti.inputs.base_output_dir,subject)

    #with os.system('text') you're able to state the command 'text' in your terminal
    #therefore we use mv to move the date
    os.system('mv %s %s'%(from_path, to_path))

#to delete the workingdirectory
os.system('rm -rf %s'%prepareflow.base_dir)