Global configuration

You can set global configuration of AMICO by calling the set_config() method of the Evaluation class:

import amico

ae = amico.Evaluation()
ae.set_config('config_name', value)

General configuration parameters

peaks_filename
Peaks filename containing the main diffusion orientations. If None, the main diffusion orientations are computed using the diffusion tensor model of dipy. (default is None)

doNormalizeSignal
Normalize the signal to the b0 value. (default is True)

doKeepb0Intact
Keep the b0 image intact in the predicted signal. (default is False)

doComputeRMSE
Compute the root mean square error between the predicted and the measured signal. (default is False)

doComputeNRMSE
Compute the normalized root mean square error between the predicted and the measured signal. (default is False)

doMergeB0
Merge the b0 images into a single volume. (default is False)

doDebiasSignal
Remove Rician bias from the signal. See the Removing rician bias before fitting section for more information. (default is False)

DWI-SNR
Signal-to-noise ratio of the DWI data (SNR = b0/sigma). See the Removing rician bias before fitting section for more information. (default is None)

Warning

This parameter must be set if the doDebiasSignal parameter is set to True

Model-specific configuration parameters

NODDI

doSaveModulatedMaps
Save the modulated NDI and ODI maps for tissue-weighted means described in Parker, Christopher S. et al. 2021. (default is False)

FreeWater

doSaveCorrectedDWI
Save the corrected DWI. (default is False)

SANDI

doDirectionalAverage
Perform the directional average of the signal of each shell. (default is False)

Warning

This parameter must be set to True if you want to use the SANDI model

Advanced configuration parameters

Warning

The following parameters should be used with caution. If you are not sure about what you are doing, please leave them to their default values

DTI_fit_method
Fit method for the diffusion tensor model. Possible values are OLS (ordinary least squares) and WLS (weighted least squares). (default is OLS)

nthreads
Number of threads to use during the model fitting. If -1 the number of threads is set to the number of available CPUs in the system. See the Multithreading section for more information. (default is -1)

BLAS_nthreads
Number of threads to use in the threadpool-backend of common BLAS implementations. If -1 the number of threads is set to the number of available CPUs in the system. See the Multithreading section for more information. (dafault is 1)