qsirecon.interfaces.recon_scalars module
Classes that collect scalar images and metadata from Recon Workflows
- class qsirecon.interfaces.recon_scalars.AMICOReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
ReconScalars- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
directions (a pathlike object or string representing an existing file)
directions_metadata (a dictionary with keys which are any value and with values which are any value)
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])icvf (a pathlike object or string representing an existing file)
icvf_metadata (a dictionary with keys which are any value and with values which are any value)
isovf (a pathlike object or string representing an existing file)
isovf_metadata (a dictionary with keys which are any value and with values which are any value)
model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
modulated_icvf (a pathlike object or string representing an existing file)
modulated_icvf_metadata (a dictionary with keys which are any value and with values which are any value)
modulated_od (a pathlike object or string representing an existing file)
modulated_od_metadata (a dictionary with keys which are any value and with values which are any value)
nrmse (a pathlike object or string representing an existing file)
nrmse_metadata (a dictionary with keys which are any value and with values which are any value)
od (a pathlike object or string representing an existing file)
od_metadata (a dictionary with keys which are any value and with values which are any value)
rmse (a pathlike object or string representing an existing file)
rmse_metadata (a dictionary with keys which are any value and with values which are any value)
tf (a pathlike object or string representing an existing file)
tf_metadata (a dictionary with keys which are any value and with values which are any value)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {'directions': {'bids': {'model': 'noddi', 'param': 'direction'}, 'metadata': {'Description': 'Peak directions from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'OrientationEncoding': {'EncodingAxis': 3, 'Reference': 'xyz', 'Type': 'unit3vector'}}, 'reorient_on_resample': True}, 'icvf': {'bids': {'model': 'noddi', 'param': 'icvf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Intracellular volume fraction (Neurite Density Index; NDI) from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/22484410'}}, 'isovf': {'bids': {'model': 'noddi', 'param': 'isovf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Isotropic volume fraction (Freewater Fraction; FWF) from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/22484410'}}, 'modulated_icvf': {'bids': {'desc': 'modulated', 'model': 'noddi', 'param': 'icvf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Intracellular volume fraction modulated by tissue fraction (ICVF * tissue fraction) from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/34852276'}}, 'modulated_od': {'bids': {'desc': 'modulated', 'model': 'noddi', 'param': 'od'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Orientation dispersion index modulated by tissue fraction (OD * tissue fraction) from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/34852276'}}, 'nrmse': {'bids': {'model': 'noddi', 'param': 'nrmse'}, 'figure': {'vmin': 0}, 'metadata': {'Description': 'Normalized root mean square error between predicted and measured signal from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}}}, 'od': {'bids': {'model': 'noddi', 'param': 'od'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Orientation dispersion index (ODI) from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/22484410'}}, 'rmse': {'bids': {'model': 'noddi', 'param': 'rmse'}, 'figure': {'vmin': 0}, 'metadata': {'Description': 'Root mean square error between predicted and measured signal from AMICO NODDI', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}}}, 'tf': {'bids': {'model': 'noddi', 'param': 'tf'}, 'figure': {'vmax': 1, 'vmin': 0}, 'metadata': {'Description': 'Tissue fraction (1 - isotropic volume fraction) computed by QSIRecon', 'Model': {'Description': 'Neurite Orientation Dispersion and Density Imaging (NODDI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/25462697'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/34852276'}}}
- class qsirecon.interfaces.recon_scalars.BrainSuite3dSHOREReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
ReconScalars- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
alpha_image (a pathlike object or string representing an existing file)
alpha_image_metadata (a dictionary with keys which are any value and with values which are any value)
cnr_image (a pathlike object or string representing an existing file)
cnr_image_metadata (a dictionary with keys which are any value and with values which are any value)
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])lapnorm_file (a pathlike object or string representing an existing file)
lapnorm_file_metadata (a dictionary with keys which are any value and with values which are any value)
mapcoeffs_file (a pathlike object or string representing an existing file)
mapcoeffs_file_metadata (a dictionary with keys which are any value and with values which are any value)
model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
msd_file (a pathlike object or string representing an existing file)
msd_file_metadata (a dictionary with keys which are any value and with values which are any value)
ng_file (a pathlike object or string representing an existing file)
ng_file_metadata (a dictionary with keys which are any value and with values which are any value)
ngpar_file (a pathlike object or string representing an existing file)
ngpar_file_metadata (a dictionary with keys which are any value and with values which are any value)
ngperp_file (a pathlike object or string representing an existing file)
ngperp_file_metadata (a dictionary with keys which are any value and with values which are any value)
qiv_file (a pathlike object or string representing an existing file)
qiv_file_metadata (a dictionary with keys which are any value and with values which are any value)
r2_image (a pathlike object or string representing an existing file)
r2_image_metadata (a dictionary with keys which are any value and with values which are any value)
regularization_image (a pathlike object or string representing an existing file)
regularization_image_metadata (a dictionary with keys which are any value and with values which are any value)
rtap_file (a pathlike object or string representing an existing file)
rtap_file_metadata (a dictionary with keys which are any value and with values which are any value)
rtop_file (a pathlike object or string representing an existing file)
rtop_file_metadata (a dictionary with keys which are any value and with values which are any value)
rtpp_file (a pathlike object or string representing an existing file)
rtpp_file_metadata (a dictionary with keys which are any value and with values which are any value)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {'alpha_image': {'bids': {'model': '3dshore', 'param': 'alpha'}, 'metadata': {'Description': 'alpha used when fitting in each voxel'}}, 'cnr_image': {'bids': {'model': '3dshore', 'param': 'CNR'}, 'metadata': {'Description': 'Contrast to noise ratio for 3dshore fit'}}, 'lapnorm_file': {'bids': {'model': '3dshore', 'param': 'lapnorm'}, 'metadata': {'Description': 'Laplacian norm from regularized MAPMRI (MAPL)'}}, 'mapcoeffs_file': {'bids': {'model': '3dshore', 'param': 'mapcoeffs'}, 'metadata': {'Description': 'MAPMRI coefficients'}}, 'msd_file': {'bids': {'model': '3dshore', 'param': 'msd'}, 'metadata': {'Description': 'mean square displacement from MAPMRI'}}, 'ng_file': {'bids': {'model': '3dshore', 'param': 'ng'}, 'metadata': {'Description': 'Non-Gaussianity from MAPMRI'}}, 'ngpar_file': {'bids': {'model': '3dshore', 'param': 'ngpar'}, 'metadata': {'Description': 'Non-Gaussianity parallel from MAPMRI'}}, 'ngperp_file': {'bids': {'model': '3dshore', 'param': 'ngperp'}, 'metadata': {'Description': 'Non-Gaussianity perpendicular from MAPMRI'}}, 'qiv_file': {'bids': {'model': '3dshore', 'param': 'qiv'}, 'metadata': {'Description': 'q-space inverse variance from MAPMRI'}}, 'r2_image': {'bids': {'model': '3dshore', 'param': 'r2'}, 'metadata': {'Description': 'r^2 of the 3dshore fit'}}, 'regularization_image': {'bids': {'model': '3dshore', 'param': 'regularization'}, 'metadata': {'Description': 'regularization of the 3dshore fit'}}, 'rtap_file': {'bids': {'model': '3dshore', 'param': 'rtap'}, 'metadata': {'Description': 'Return to axis probability from MAPMRI'}}, 'rtop_file': {'bids': {'model': '3dshore', 'param': 'rtop'}, 'metadata': {'Description': 'Return to origin probability from MAPMRI'}}, 'rtpp_file': {'bids': {'model': '3dshore', 'param': 'rtpp'}, 'metadata': {'Description': 'Return to plane probability from MAPMRI'}}}
- class qsirecon.interfaces.recon_scalars.DIPYDKIReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
ReconScalars- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])dki_ad (a pathlike object or string representing an existing file)
dki_ad_metadata (a dictionary with keys which are any value and with values which are any value)
dki_ak (a pathlike object or string representing an existing file)
dki_ak_metadata (a dictionary with keys which are any value and with values which are any value)
dki_fa (a pathlike object or string representing an existing file)
dki_fa_metadata (a dictionary with keys which are any value and with values which are any value)
dki_kfa (a pathlike object or string representing an existing file)
dki_kfa_metadata (a dictionary with keys which are any value and with values which are any value)
dki_linearity (a pathlike object or string representing an existing file)
dki_linearity_metadata (a dictionary with keys which are any value and with values which are any value)
dki_md (a pathlike object or string representing an existing file)
dki_md_metadata (a dictionary with keys which are any value and with values which are any value)
dki_mk (a pathlike object or string representing an existing file)
dki_mk_metadata (a dictionary with keys which are any value and with values which are any value)
dki_mkt (a pathlike object or string representing an existing file)
dki_mkt_metadata (a dictionary with keys which are any value and with values which are any value)
dki_planarity (a pathlike object or string representing an existing file)
dki_planarity_metadata (a dictionary with keys which are any value and with values which are any value)
dki_rd (a pathlike object or string representing an existing file)
dki_rd_metadata (a dictionary with keys which are any value and with values which are any value)
dki_rk (a pathlike object or string representing an existing file)
dki_rk_metadata (a dictionary with keys which are any value and with values which are any value)
dki_sphericity (a pathlike object or string representing an existing file)
dki_sphericity_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_ad (a pathlike object or string representing an existing file)
dkimicro_ad_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_ade (a pathlike object or string representing an existing file)
dkimicro_ade_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_ak (a pathlike object or string representing an existing file)
dkimicro_ak_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_awf (a pathlike object or string representing an existing file)
dkimicro_awf_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_axonald (a pathlike object or string representing an existing file)
dkimicro_axonald_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_kfa (a pathlike object or string representing an existing file)
dkimicro_kfa_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_md (a pathlike object or string representing an existing file)
dkimicro_md_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_rd (a pathlike object or string representing an existing file)
dkimicro_rd_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_rde (a pathlike object or string representing an existing file)
dkimicro_rde_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_tortuosity (a pathlike object or string representing an existing file)
dkimicro_tortuosity_metadata (a dictionary with keys which are any value and with values which are any value)
dkimicro_trace (a pathlike object or string representing an existing file)
dkimicro_trace_metadata (a dictionary with keys which are any value and with values which are any value)
model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
msdki_awf (a pathlike object or string representing an existing file)
msdki_awf_metadata (a dictionary with keys which are any value and with values which are any value)
msdki_di (a pathlike object or string representing an existing file)
msdki_di_metadata (a dictionary with keys which are any value and with values which are any value)
msdki_mfa (a pathlike object or string representing an existing file)
msdki_mfa_metadata (a dictionary with keys which are any value and with values which are any value)
msdki_msd (a pathlike object or string representing an existing file)
msdki_msd_metadata (a dictionary with keys which are any value and with values which are any value)
msdki_msk (a pathlike object or string representing an existing file)
msdki_msk_metadata (a dictionary with keys which are any value and with values which are any value)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {'dki_ad': {'bids': {'model': 'dki', 'param': 'ad'}, 'metadata': {'Description': 'DKI axial diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/', 'Units': 'mm^2/s'}}, 'dki_ak': {'bids': {'model': 'dki', 'param': 'ak'}, 'metadata': {'Description': 'DKI axial kurtosis', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/'}}, 'dki_fa': {'bids': {'model': 'dki', 'param': 'fa'}, 'metadata': {'Description': 'DKI fractional anisotropy', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/'}}, 'dki_kfa': {'bids': {'model': 'dki', 'param': 'kfa'}, 'metadata': {'Description': 'DKI kurtosis fractional anisotropy', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/'}}, 'dki_linearity': {'bids': {'model': 'dki', 'param': 'linearity'}, 'metadata': {'Description': 'DKI linearity', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/'}}, 'dki_md': {'bids': {'model': 'dki', 'param': 'md'}, 'metadata': {'Description': 'DKI mean diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/', 'Units': 'mm^2/s'}}, 'dki_mk': {'bids': {'model': 'dki', 'param': 'mk'}, 'metadata': {'Description': 'DKI mean kurtosis', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/'}}, 'dki_mkt': {'bids': {'model': 'dki', 'param': 'mkt'}, 'metadata': {'Description': 'DKI mean of the kurtosis tensor', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/23589312/'}}, 'dki_planarity': {'bids': {'model': 'dki', 'param': 'planarity'}, 'metadata': {'Description': 'DKI planarity'}}, 'dki_rd': {'bids': {'model': 'dki', 'param': 'rd'}, 'metadata': {'Description': 'DKI radial diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/', 'Units': 'mm^2/s'}}, 'dki_rk': {'bids': {'model': 'dki', 'param': 'rk'}, 'metadata': {'Description': 'DKI radial kurtosis', 'Model': {'Description': 'Diffusion Kurtosis Imaging (DKI)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21337412/'}}, 'dki_sphericity': {'bids': {'model': 'dki', 'param': 'sphericity'}, 'metadata': {'Description': 'DKI sphericity'}}, 'dkimicro_ad': {'bids': {'model': 'dkimicro', 'param': 'ad'}, 'metadata': {'Description': 'DKI Microstructural Axial Diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'dkimicro_ade': {'bids': {'model': 'dkimicro', 'param': 'ade'}, 'metadata': {'Description': 'DKI Microstructural Axial Diffusivity of the Extra-Cellular Compartment', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'dkimicro_ak': {'bids': {'model': 'dkimicro', 'param': 'ak'}, 'metadata': {'Description': 'DKI Microstructural Axial Kurtosis', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/'}}, 'dkimicro_awf': {'bids': {'model': 'dkimicro', 'param': 'awf'}, 'metadata': {'Description': 'DKI axonal water fraction', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/'}}, 'dkimicro_axonald': {'bids': {'model': 'dkimicro', 'param': 'axonald'}, 'metadata': {'Description': 'DKI Microstructural Axonal Diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'dkimicro_kfa': {'bids': {'model': 'dkimicro', 'param': 'kfa'}, 'metadata': {'Description': 'DKI Microstructural Kurtosis Fractional Anisotropy', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/'}}, 'dkimicro_md': {'bids': {'model': 'dkimicro', 'param': 'md'}, 'metadata': {'Description': 'DKI Microstructural Mean Diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'dkimicro_rd': {'bids': {'model': 'dkimicro', 'param': 'rd'}, 'metadata': {'Description': 'DKI Microstructural Radial Diffusivity', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'dkimicro_rde': {'bids': {'model': 'dkimicro', 'param': 'rde'}, 'metadata': {'Description': 'DKI radial diffusivity of the extra-cellular compartment', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'dkimicro_tortuosity': {'bids': {'model': 'dkimicro', 'param': 'tortuosity'}, 'metadata': {'Description': 'DKI Microstructural Tortuosity', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/'}}, 'dkimicro_trace': {'bids': {'model': 'dkimicro', 'param': 'trace'}, 'metadata': {'Description': 'DKI Microstructural Trace', 'Model': {'Description': 'Diffusion Kurtosis Microstructural Imaging (DKI-MICRO)', 'URL': 'https://pubmed.ncbi.nlm.nih.gov/34349631/'}, 'ParameterURL': 'https://pubmed.ncbi.nlm.nih.gov/21699989/', 'Units': 'mm^2/s'}}, 'msdki_awf': {'bids': {'model': 'msdki', 'param': 'awf'}, 'metadata': {'Description': 'MSDKI Axonal Water Fraction from the mean signal diffusional kurtosis parameters assuming the 2-compartmental spherical mean technique model.'}}, 'msdki_di': {'bids': {'model': 'msdki', 'param': 'di'}, 'metadata': {'Description': 'MSDKI intrinsic diffusivity from the mean signal diffusional kurtosis parameters assuming the 2-compartmental spherical mean technique model.'}}, 'msdki_mfa': {'bids': {'model': 'msdki', 'param': 'mfa'}, 'metadata': {'Description': 'MSDKI Microscopic Fractional Anisotropy from the mean signal diffusional kurtosis parameters assuming the 2-compartmental spherical mean technique model.'}}, 'msdki_msd': {'bids': {'model': 'msdki', 'param': 'msd'}, 'metadata': {'Description': 'MSDKI Mean Signal Diffusivity'}}, 'msdki_msk': {'bids': {'model': 'msdki', 'param': 'msk'}, 'metadata': {'Description': 'MSDKI Mean Signal Kurtosis'}}}
- class qsirecon.interfaces.recon_scalars.DIPYMAPMRIReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
ReconScalars- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])lapnorm (a pathlike object or string representing an existing file)
lapnorm_metadata (a dictionary with keys which are any value and with values which are any value)
mapcoeffs (a pathlike object or string representing an existing file)
mapcoeffs_metadata (a dictionary with keys which are any value and with values which are any value)
model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
msd (a pathlike object or string representing an existing file)
msd_metadata (a dictionary with keys which are any value and with values which are any value)
ng (a pathlike object or string representing an existing file)
ng_metadata (a dictionary with keys which are any value and with values which are any value)
ngpar (a pathlike object or string representing an existing file)
ngpar_metadata (a dictionary with keys which are any value and with values which are any value)
ngperp (a pathlike object or string representing an existing file)
ngperp_metadata (a dictionary with keys which are any value and with values which are any value)
qiv (a pathlike object or string representing an existing file)
qiv_metadata (a dictionary with keys which are any value and with values which are any value)
rtap (a pathlike object or string representing an existing file)
rtap_metadata (a dictionary with keys which are any value and with values which are any value)
rtop (a pathlike object or string representing an existing file)
rtop_metadata (a dictionary with keys which are any value and with values which are any value)
rtpp (a pathlike object or string representing an existing file)
rtpp_metadata (a dictionary with keys which are any value and with values which are any value)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {'lapnorm': {'bids': {'model': 'mapmri', 'param': 'lapnorm'}, 'metadata': {'Description': 'Laplacian norm from regularized MAPMRI (MAPL)', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'mapcoeffs': {'bids': {'model': 'mapmri', 'param': 'mapcoeffs'}, 'metadata': {'Description': 'MAPMRI coefficients', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'msd': {'bids': {'model': 'mapmri', 'param': 'msd'}, 'metadata': {'Description': 'Mean square displacement from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'ng': {'bids': {'model': 'mapmri', 'param': 'ng'}, 'metadata': {'Description': 'Non-Gaussianity from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'ngpar': {'bids': {'model': 'mapmri', 'param': 'ngpar'}, 'metadata': {'Description': 'Non-Gaussianity parallel from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'ngperp': {'bids': {'model': 'mapmri', 'param': 'ngperp'}, 'metadata': {'Description': 'Non-Gaussianity perpendicular from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'qiv': {'bids': {'model': 'mapmri', 'param': 'qiv'}, 'metadata': {'Description': 'q-space inverse variance from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'rtap': {'bids': {'model': 'mapmri', 'param': 'rtap'}, 'metadata': {'Description': 'Return to axis probability from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'rtop': {'bids': {'model': 'mapmri', 'param': 'rtop'}, 'metadata': {'Description': 'Return to origin probability from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'rtpp': {'bids': {'model': 'mapmri', 'param': 'rtpp'}, 'metadata': {'Description': 'Return to plane probability from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}}
- class qsirecon.interfaces.recon_scalars.DSIStudioReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
ReconScalars- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
ad_file (a pathlike object or string representing an existing file)
ad_file_metadata (a dictionary with keys which are any value and with values which are any value)
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])dti_fa_file (a pathlike object or string representing an existing file)
dti_fa_file_metadata (a dictionary with keys which are any value and with values which are any value)
gfa_file (a pathlike object or string representing an existing file)
gfa_file_metadata (a dictionary with keys which are any value and with values which are any value)
ha_file (a pathlike object or string representing an existing file)
ha_file_metadata (a dictionary with keys which are any value and with values which are any value)
iso_file (a pathlike object or string representing an existing file)
iso_file_metadata (a dictionary with keys which are any value and with values which are any value)
md_file (a pathlike object or string representing an existing file)
md_file_metadata (a dictionary with keys which are any value and with values which are any value)
model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
nrdi02L_file (a pathlike object or string representing an existing file)
nrdi02L_file_metadata (a dictionary with keys which are any value and with values which are any value)
nrdi04L_file (a pathlike object or string representing an existing file)
nrdi04L_file_metadata (a dictionary with keys which are any value and with values which are any value)
nrdi06L_file (a pathlike object or string representing an existing file)
nrdi06L_file_metadata (a dictionary with keys which are any value and with values which are any value)
qa_file (a pathlike object or string representing an existing file)
qa_file_metadata (a dictionary with keys which are any value and with values which are any value)
rd1_file (a pathlike object or string representing an existing file)
rd1_file_metadata (a dictionary with keys which are any value and with values which are any value)
rd2_file (a pathlike object or string representing an existing file)
rd2_file_metadata (a dictionary with keys which are any value and with values which are any value)
rd_file (a pathlike object or string representing an existing file)
rd_file_metadata (a dictionary with keys which are any value and with values which are any value)
rdi_file (a pathlike object or string representing an existing file)
rdi_file_metadata (a dictionary with keys which are any value and with values which are any value)
txx_file (a pathlike object or string representing an existing file)
txx_file_metadata (a dictionary with keys which are any value and with values which are any value)
txy_file (a pathlike object or string representing an existing file)
txy_file_metadata (a dictionary with keys which are any value and with values which are any value)
txz_file (a pathlike object or string representing an existing file)
txz_file_metadata (a dictionary with keys which are any value and with values which are any value)
tyy_file (a pathlike object or string representing an existing file)
tyy_file_metadata (a dictionary with keys which are any value and with values which are any value)
tyz_file (a pathlike object or string representing an existing file)
tyz_file_metadata (a dictionary with keys which are any value and with values which are any value)
tzz_file (a pathlike object or string representing an existing file)
tzz_file_metadata (a dictionary with keys which are any value and with values which are any value)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {'ad_file': {'bids': {'model': 'tensor', 'param': 'ad'}, 'metadata': {'Description': 'Axial Diffusivity from a tensor fit. The first eigenvalue of the tensor.', 'Units': 'μm^2/ms'}}, 'dti_fa_file': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'Fractional Anisotropy from a tensor fit'}}, 'gfa_file': {'bids': {'model': 'gqi', 'param': 'gfa'}, 'metadata': {'Description': 'Generalized Fractional Anisotropy from a GQI fit'}}, 'ha_file': {'bids': {'model': 'tensor', 'param': 'ha'}, 'metadata': {'Description': 'Helix Angle from a tensor fit'}}, 'iso_file': {'bids': {'model': 'gqi', 'param': 'iso'}, 'metadata': {'Description': 'Isotropic Diffusion from a GQI fit'}}, 'md_file': {'bids': {'model': 'tensor', 'param': 'md'}, 'metadata': {'Description': 'Mean Diffusivity from a tensor fit. The mean of the three eigenvalues.', 'Units': 'μm^2/ms'}}, 'nrdi02L_file': {'bids': {'model': 'gqi', 'param': 'nrdi02L'}, 'metadata': {'Description': 'Non-restricted Diffusion Imaging from a GQI fit. The total amount of non-restricted diffusion regardless of orientation at a 0.2 diffusion sampling length ratio.'}}, 'nrdi04L_file': {'bids': {'model': 'gqi', 'param': 'nrdi04L'}, 'metadata': {'Description': 'Non-restricted Diffusion Imaging from a GQI fit. The total amount of non-restricted diffusion regardless of orientation at a 0.4 diffusion sampling length ratio.'}}, 'nrdi06L_file': {'bids': {'model': 'gqi', 'param': 'nrdi06L'}, 'metadata': {'Description': 'Non-restricted Diffusion Imaging from a GQI fit. The total amount of non-restricted diffusion regardless of orientation at a 0.6 diffusion sampling length ratio.'}}, 'qa_file': {'bids': {'model': 'gqi', 'param': 'qa'}, 'metadata': {'Description': 'Quantitative Anisotropy from a GQI fit'}}, 'rd1_file': {'bids': {'model': 'tensor', 'param': 'rd1'}, 'metadata': {'Description': 'Lambda 2 (second eigenvalue) from a tensor fit.', 'Units': 'μm^2/ms'}}, 'rd2_file': {'bids': {'model': 'tensor', 'param': 'rd2'}, 'metadata': {'Description': 'Lambda 3 (third eigenvalue) from a tensor fit.', 'Units': 'μm^2/ms'}}, 'rd_file': {'bids': {'model': 'tensor', 'param': 'rd'}, 'metadata': {'Description': 'Radial Diffusivity from a tensor fit. The mean of the second and third eigenvalues (rd1 and rd2).', 'Units': 'μm^2/ms'}}, 'rdi_file': {'bids': {'model': 'gqi', 'param': 'rdi'}, 'metadata': {'Description': 'Restricted Diffusion Imaging from a GQI fit. Indexes the the total amount of restricted diffusion regardless of orientation.'}}, 'txx_file': {'bids': {'model': 'tensor', 'param': 'txx'}, 'metadata': {'Description': 'Tensor fit txx'}}, 'txy_file': {'bids': {'model': 'tensor', 'param': 'txy'}, 'metadata': {'Description': 'Tensor fit txy'}}, 'txz_file': {'bids': {'model': 'tensor', 'param': 'txz'}, 'metadata': {'Description': 'Tensor fit txz'}}, 'tyy_file': {'bids': {'model': 'tensor', 'param': 'tyy'}, 'metadata': {'Description': 'Tensor fit tyy'}}, 'tyz_file': {'bids': {'model': 'tensor', 'param': 'tyz'}, 'metadata': {'Description': 'Tensor fit tyz'}}, 'tzz_file': {'bids': {'model': 'tensor', 'param': 'tzz'}, 'metadata': {'Description': 'Tensor fit tzz'}}}
- class qsirecon.interfaces.recon_scalars.DisorganizeScalarData(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
SimpleInterface- Optional Inputs:
scalar_config (a dictionary with keys which are any value and with values which are any value)
scalar_file (a pathlike object or string representing an existing file)
- Outputs:
scalar_config (a dictionary with keys which are any value and with values which are any value)
- class qsirecon.interfaces.recon_scalars.OrganizeScalarData(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
SimpleInterface- Optional Inputs:
scalar_config (a dictionary with keys which are any value and with values which are any value)
- Outputs:
desc (a string or a _Undefined or None or None)
metadata (a dictionary with keys which are any value and with values which are any value)
model (a string or a _Undefined or None)
param (a string or a _Undefined or None)
scalar_file (a pathlike object or string representing an existing file)
- class qsirecon.interfaces.recon_scalars.ParcellateScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
SimpleInterface- Optional Inputs:
atlas_config (a dictionary with keys which are any value and with values which are any value)
brain_mask (a pathlike object or string representing an existing file)
mapping_metadata (a dictionary with keys which are any value and with values which are any value) – Info about the upstream workflow that created the anatomical mapping units.
scalars_config (a list of items which are a dictionary with keys which are any value and with values which are any value)
scalars_from (a list of items which are a string)
- Outputs:
metadata (a dictionary with keys which are any value and with values which are any value)
parcellated_scalar_tsv (a pathlike object or string representing an existing file)
seg (a string)
- class qsirecon.interfaces.recon_scalars.ParcellationTableSplitterDataSink(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
SimpleInterface- Mandatory Inputs:
in_file (a pathlike object or string representing an existing file) – Tsv of combined scalar summaries.
seg (a string) – The name of the segmentation.
source_file (a pathlike object or string representing a file) – The source file(s) to extract entities from.
- Optional Inputs:
base_directory (a string or os.PathLike object) – Path to the base directory for storing data.
compress (a boolean) – (Nipype default value:
False)dataset_links (a dictionary with keys which are any value and with values which are any value) – Dataset links.
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])meta_dict (a dictionary with keys which are any value and with values which are any value) – Metadata dictionary.
suffix (a string) – The suffix of the parcellated data. (Nipype default value:
dwimap)
- Outputs:
out_file (a list of items which are a pathlike object or string representing an existing file)
out_meta (a list of items which are a pathlike object or string representing an existing file)
- class qsirecon.interfaces.recon_scalars.ReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
SimpleInterface- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {}
- class qsirecon.interfaces.recon_scalars.ReconScalarsTableSplitterDataSink(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
SimpleInterface- Mandatory Inputs:
suffix (a string)
summary_tsv (a pathlike object or string representing an existing file) – Tsv of combined scalar summaries.
- Optional Inputs:
base_directory (a pathlike object or string representing a file)
compress (a boolean) – (Nipype default value:
True)dismiss_entities (a list of items which are any value) – (Nipype default value:
[])infer_suffix (a boolean) – (Nipype default value:
False)metadata (a dictionary with keys which are any value and with values which are any value) – List of metadata dictionaries.
recon_scalars (a list of items which are any value)
resampled_files (a list of items which are a pathlike object or string representing an existing file) – Resampled scalar files. This field is not used, but we keep it so that the files won’t be automatically deleted by Nipype.
source_file (a pathlike object or string representing a file)
- class qsirecon.interfaces.recon_scalars.TORTOISEReconScalars(from_file=None, resource_monitor=None, **inputs)[source]
Bases:
ReconScalars- Mandatory Inputs:
qsirecon_suffix (a string)
source_file (a pathlike object or string representing an existing file)
- Optional Inputs:
ad_file (a pathlike object or string representing an existing file)
ad_file_metadata (a dictionary with keys which are any value and with values which are any value)
am_file (a pathlike object or string representing an existing file)
am_file_metadata (a dictionary with keys which are any value and with values which are any value)
dismiss_entities (a list of items which are any value) – (Nipype default value:
[])fa_file (a pathlike object or string representing an existing file)
fa_file_metadata (a dictionary with keys which are any value and with values which are any value)
li_file (a pathlike object or string representing an existing file)
li_file_metadata (a dictionary with keys which are any value and with values which are any value)
md (a pathlike object or string representing an existing file)
md_metadata (a dictionary with keys which are any value and with values which are any value)
model_info (a dictionary with keys which are any value and with values which are any value)
model_name (a string)
ng_file (a pathlike object or string representing an existing file)
ng_file_metadata (a dictionary with keys which are any value and with values which are any value)
ngpar_file (a pathlike object or string representing an existing file)
ngpar_file_metadata (a dictionary with keys which are any value and with values which are any value)
ngperp_file (a pathlike object or string representing an existing file)
ngperp_file_metadata (a dictionary with keys which are any value and with values which are any value)
pa_file (a pathlike object or string representing an existing file)
pa_file_metadata (a dictionary with keys which are any value and with values which are any value)
path_file (a pathlike object or string representing an existing file)
path_file_metadata (a dictionary with keys which are any value and with values which are any value)
rd_file (a pathlike object or string representing an existing file)
rd_file_metadata (a dictionary with keys which are any value and with values which are any value)
rtap_file (a pathlike object or string representing an existing file)
rtap_file_metadata (a dictionary with keys which are any value and with values which are any value)
rtop_file (a pathlike object or string representing an existing file)
rtop_file_metadata (a dictionary with keys which are any value and with values which are any value)
rtpp_file (a pathlike object or string representing an existing file)
rtpp_file_metadata (a dictionary with keys which are any value and with values which are any value)
- Outputs:
scalar_info (a list of items which are any value)
- scalar_metadata = {'ad_file': {'bids': {'model': 'tensor', 'param': 'ad'}, 'metadata': {'Description': 'Axial Diffusivity from a tensor fit'}}, 'am_file': {'bids': {'model': 'tensor', 'param': 'am'}, 'metadata': {'Description': 'A0 from a tensor fit'}}, 'fa_file': {'bids': {'model': 'tensor', 'param': 'fa'}, 'metadata': {'Description': 'Fractional Anisotropy from a tensor fit'}}, 'li_file': {'bids': {'model': 'tensor', 'param': 'li'}, 'metadata': {'Description': 'LI from a tensor fit'}}, 'md': {'bids': {'model': 'tensor', 'param': 'md'}, 'metadata': {'Description': 'Mean Diffusivity from a tensor fit', 'Model': {'Description': 'Custom Python code implementing the formula (ad + (2 * rd)) / 3'}}}, 'ng_file': {'bids': {'model': 'mapmri', 'param': 'ng'}, 'metadata': {'Description': 'Non-Gaussianity from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'ngpar_file': {'bids': {'model': 'mapmri', 'param': 'ngpar'}, 'metadata': {'Description': 'Non-Gaussianity parallel from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'ngperp_file': {'bids': {'model': 'mapmri', 'param': 'ngperp'}, 'metadata': {'Description': 'Non-Gaussianity perpendicular from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'pa_file': {'bids': {'model': 'mapmri', 'param': 'pa'}, 'metadata': {'Description': 'PA from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'path_file': {'bids': {'model': 'mapmri', 'param': 'path'}, 'metadata': {'Description': 'Path from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'rd_file': {'bids': {'model': 'tensor', 'param': 'rd'}, 'metadata': {'Description': 'Radial Diffusivity from a tensor fit'}}, 'rtap_file': {'bids': {'model': 'mapmri', 'param': 'rtap'}, 'metadata': {'Description': 'Return to axis probability from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'rtop_file': {'bids': {'model': 'mapmri', 'param': 'rtop'}, 'metadata': {'Description': 'Return to origin probability from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}, 'rtpp_file': {'bids': {'model': 'mapmri', 'param': 'rtpp'}, 'metadata': {'Description': 'Return to plane probability from MAPMRI', 'Model': {'Description': 'Mean Apparent Propagator MRI (MAPMRI) with Laplacian regularization', 'URL': 'https://doi.org/10.1016/j.neuroimage.2013.04.016'}}}}