FreeSurfer

Module contents

Input and output specification dicationaries for FreeSurfer analyses.

Submodules

django_mri.analysis.specifications.freesurfer.recon_all module

Input and output specification dictionaries for FreeSurfer’s recon_all script.

django_mri.analysis.specifications.freesurfer.recon_all.RECON_ALL_INPUT_SPECIFICATION = {'FLAIR_file': {'description': 'Path to FLAIR image to be used for improved pial surface estimation (can be either a DICOM, MGH or NIFTI file)', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'T1_files': {'description': 'A list of T1 files to be processed, in either DICOM or NIfTI format.', 'element_type': 'FIL', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'T2_file': {'description': 'Path to T2 image to be used for improved pial surface estimation (can be either a DICOM, MGH or NIFTI file)', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'big_ventricles': {'description': 'To be used for subjects with enlarged ventricles.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'brainstem': {'description': 'Segment brainstem structures.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'directive': {'choices': ['all', 'autorecon1', 'autorecon2', 'autorecon2-volonly', 'autorecon2-perhemi', 'autorecon2-inflate1', 'autorecon2-cp', 'autorecon2-wm', 'autorecon3', 'autorecon3-T2pial', 'autorecon-pial', 'autorecon-hemi', 'localGI', 'qcache'], 'default': 'all', 'description': 'Directives control the execution of the various processing procedures carried out.', 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'expert': {'description': 'Set parameters using an expert file.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.file_input_definition.FileInputDefinition'>}, 'flags': {'description': 'Additional parameters.', 'element_type': 'STR', 'required': False, 'type': <class 'django_analyses.models.input.definitions.list_input_definition.ListInputDefinition'>}, 'hemi': {'choices': ['lh', 'rh'], 'description': 'Choose to run only for a particular hemisphere.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'hippocampal_subfields_T1': {'description': 'Segment hippocampal subfields using the T1 image.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'hires': {'description': 'Conform to minimum voxel size (for voxels lesser than 1mm).', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'mprage': {'description': 'Assume scan parameters are MGH MPRAGE protocol, which produces darker grey matter.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'mri_aparc2aseg': {'description': 'Flags to pass to mri_aparc2aseg commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_ca_label': {'description': 'Flags to pass to mri_ca_label commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_ca_normalize': {'description': 'Flags to pass to mri_ca_normalize commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_ca_register': {'description': 'Flags to pass to mri_ca_register commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_edit_wm_with_aseg': {'description': 'Flags to pass to mri_edit_wm_with_aseg commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_em_register': {'description': 'Flags to pass to mri_em_register commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_fill': {'description': 'Flags to pass to mri_fill commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_mask': {'description': 'Flags to pass to mri_mask commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_normalize': {'description': 'Flags to pass to mri_normalize commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_pretess': {'description': 'Flags to pass to mri_pretess commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_remove_neck': {'description': 'Flags to pass to mri_remove_neck commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_segment': {'description': 'Flags to pass to mri_segment commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_segstats': {'description': 'Flags to pass to mri_segstats commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_tessellate': {'description': 'Flags to pass to mri_tessellate commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mri_watershed': {'description': 'Flags to pass to mri_watershed commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_anatomical_stats': {'description': 'Flags to pass to mris_anatomical_stats commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_ca_label': {'description': 'Flags to pass to mris_ca_label commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_fix_topology': {'description': 'Flags to pass to mris_fix_topology commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_inflate': {'description': 'Flags to pass to mris_inflate commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_make_surfaces': {'description': 'Flags to pass to mris_make_surfaces commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_register': {'description': 'Flags to pass to mris_register commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_smooth': {'description': 'Flags to pass to mris_smooth commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_sphere': {'description': 'Flags to pass to mris_sphere commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mris_surf2vol': {'description': 'Flags to pass to mris_surf2vol commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'mrisp_paint': {'description': 'Flags to pass to mrisp_paint commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'openmp': {'description': 'Number of processes to run if parallel execution is enabled.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.integer_input_definition.IntegerInputDefinition'>}, 'parallel': {'description': 'Enable parallel execution.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'subject_id': {'description': 'Subject ID to be searched for in the SUBJECTS_DIR path.', 'dynamic_default': '{run_id}', 'is_configuration': False, 'required': True, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'subjects_dir': {'default': '/home/docs/checkouts/readthedocs.org/user_builds/django-mri/checkouts/latest/media/analysis', 'description': 'Path to subjects directory.', 'required': True, 'type': <class 'django_analyses.models.input.definitions.directory_input_definition.DirectoryInputDefinition'>}, 'talairach': {'description': 'Flags to pass to talairach commands.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}, 'use_FLAIR': {'description': 'Whether to use the provided FLAIR image to generate an improved pial surface estimation.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'use_T2': {'description': 'Whether to use the provided T2 image to generate an improved pial surface estimation.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.boolean_input_definition.BooleanInputDefinition'>}, 'xopts': {'choices': ['use', 'clean', 'overwrite'], 'description': 'Use, clean, or overwrite the existing experts file.', 'required': False, 'type': <class 'django_analyses.models.input.definitions.string_input_definition.StringInputDefinition'>}}

recon_all input specification.

django_mri.analysis.specifications.freesurfer.recon_all.RECON_ALL_OUTPUT_SPECIFICATION = {'T1': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'aseg': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'aseg_stats': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'brain': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'brainmask': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'filled': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'norm': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'nu': {'description': "This is an intensity normalized volume generated after correcting for non-uniformity in conformed raw average (saved as 'mri/orig.mgz'). If there are any errors in later steps, it sometimes helps to check if the intensity values don't look normal in this file. If the values are too high, then scaling down the intensity a little bit and re-running recon-all usually corrects that error. In some cases, this scaling down can also be done for the orig.mgz volume.", 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'orig': {'description': 'A conformed (i.e. to 256^3, 1mm isotropic) average volume of the raw input data.', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'rawavg': {'description': 'An average volume of the raw input data (if there is only one input volume, they will be identical). This volume is unconformed (i.e. to 256^3, 1mm isotropic)', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'wm': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'wmparc': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}, 'wmparc_stats': {'description': '', 'type': <class 'django_analyses.models.output.definitions.file_output_definition.FileOutputDefinition'>}}

recon_all output specification.