insert( 0,)ĭef write_dicom_table( dicom_table, table_dir):ĭef write_by_series( json_config, input_table, output_dir): #Sort by MRN, then ACC, then Acq Time, then Series Numberīig_table = sorted( big_table, key = itemgetter( 1, 4, 5))īig_table. #print ('Key Error for '+acc+series_desc) #print (mrn,acc,os.path.join(input_dir,i,j,k),acquisition_time,series_desc) join( slugged_series_folder, dicoms_in_series))īig_table. join( slugged_series_folder, dicoms_in_series), force = True) move( series_folder_path, slugged_series_folder)ĭicoms_in_series = os. move( study_folder, slugged_study_folder)įor k in os. If config = 'CTA-2phase':ĭef make_big_table( input_dir, json_config): Print ( '****Sorted through possible crap in ' + i) #make_folder_if_absent(os.path.join(output_dir,i))įor j in os.

append( arr, arr, axis = 0)ĭef check_directory( input_dir, json_config):įor tag, series in enumerate( config): Print ( 'Confirm Spacing of New Flip-Only Routine')

# Find the files that matches the given pattermįor filename in fnmatch. dcm2nii import Dcm2niixįor rootDir, subdirs, filenames in os. # 2) After desired tags are annotated in the 'big table' manually (or in the future a more clever way) the code is run again reading this annotated 'big table' and converts tagged series acccordingly into nifits and puts then in a folder named by accession numberįrom nipype. User then assigns a tag in the column following series description that will correspond to an abbreviated output file name for a converted nifti. # 1) A csv 'big table' is created with a row for each series of each study.

# This takes DICOM files of studies with multiple series exported from Osirix (with hierarchy and non-deidentified options selected) and converts them into Nifti files in a two part process:

Osirix lite nifti to dicom