cmind.pipeline.cmind_baselineCBF_preprocess¶
Functions
cmind_baselineCBF_preprocess (output_dir, CBF_nii) |
BaselineCBF preprocessing (motion correction, intensity normalization & |
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cmind.pipeline.cmind_baselineCBF_preprocess.
cmind_baselineCBF_preprocess
(output_dir, CBF_nii, max_percent_diff=3.0, ANTS_bias_cmd=None, UCLA_flag=False, fsl_motion_outliers_cmd=None, discard_outliers=True, generate_figures=True, ForceUpdate=False, verbose=False, logger=None)[source]¶ BaselineCBF preprocessing (motion correction, intensity normalization & outlier rejection)
Parameters: output_dir : str
directory in which to store the output
CBF_nii : str
nifti image containing the 4D ASL timeseries
max_percent_diff : float, optional
any control-tag frames greater than this percentage will be automatically considered outliers. Used to intially remove high motion frames. Note: For background-suppressed ASL data, this should be set to None or 100.0. Will not be used if `discard_outliers`=False
ANTS_bias_cmd : str, optional
path to the bias field correction command to use. if None, assumes /usr/lib/ants/N4BiasFieldCorrection
UCLA_flag : bool, optional
if True, assumes order is “tag”,”control”,”tag”,... if False, assumes order is “control”, “tag”, “control”... if true, generate summary images
fsl_motion_outliers_cmd : str, optional
path to the fsl_motion_outliers_cmd_v2 shell script. If not specified will try to guess it relative to the python script location.
discard_outliers : bool, optional
unless False, will detect and discard outliers
generate_figures : bool, optional
if true, generate additional summary images
ForceUpdate : bool,optional
if True, rerun and overwrite any previously existing results
verbose : bool, optional
print additional output (to terminal and log)
logger : logging.Logger or str, optional
logging.Logger object (or string of a filename to log to)
Returns: BaselineCBF_mcf_percent_change : str
filename of the average control-tag percent change image
BaselineCBF_mcf_control_mean_N4 : str
filename of the average N4 bias-corrected control image
BaselineCBF_Meansub : str
filename of the average N4 bias-corrected control-tag image
BaselineCBF_timepoints_kept : str
textfile listing the control-tag timepoints that were kept
BaselineCBF_mcf_masked : str
filename of the ASL subtracted timeseries
BaselineCBF_N4Bias : str
filename of the N4 bias field computed from the mean control image
BaselineCBF_relmot : str
filename of the relative motion parameters during coregistration (motion-correction)
Notes