pyalfe.main

pyalfe.main#

pyalfe.main.run(accession: str, input_dir: str, output_dir: str, modalities: str = ['T1', 'T1Post', 'FLAIR', 'T2', 'ADC', 'SWI', 'CBF'], targets: str = ['FLAIR', 'T1Post'], dominant_tissue: str = 'white_matter', image_processor: str = 'nilearn', image_registration: str = 'greedy', data_dir_structure: str = 'alfe', tissue_segmentation: str = 'prior', overwrite: bool = True) → None[source]#

Runs the pipeline for an accession number.

Parameters:

  • accession (str) – the accession number for which you want to run the pipeline.

  • config (str, default: DEFAULT_CFG) – the path to the config file.

  • input_dir (str) – the path to the directory containing input images

  • output_dir (str) – the path to the directory containing output images

  • modalities (str, default: DEFAULT_MODALITIES) – comma separated modalities

  • targets (str, default: DEFAULT_TARGETS) – comma separated target modalities

  • dominant_tissue (str, default: DEFAUlT_DOMINANT_TISSUE) – dominant tissue

  • image_processor (str, default: DEFAULT_IMAGE_PROCESSOR) – image processor that is used by the pipeline.

  • image_registration (str, default: DEFAULT_IMAGE_REGISTRATION) – image registration that is used by the pipeline.

  • data_dir_structure (str, default: DEFUALT_DATA_DIR_STRUCTURE) – the data directory structure, it can be ‘alfe’ or ‘bids’.

  • tissue_segmentation (str, default: DEFAULT_TISSUE_SEGMENTATION) – the tissue segmentation method, it can be ‘prior’ or ‘synthseg’

  • overwrite (bool, default: DEFAULT_OVERWRITE) – if True, the pipeline overwrites existing output images.

Return type:

None

pyalfe.main.process_dicom(accession: str, dicom_dir: str, nifti_dir: str, data_dir_structure: str = 'alfe', overwrite: bool = True)[source]#