eXtensible Connectivity Pipeline-style quality control files

See also

User Guide: Generate eXtensible Connectivity Pipeline-style quality control files

Columns

substr

subject label [1]

sesstr

session label [1]

taskstr

task label [1]

runint

run index [1]

descstr

description [1]

regressorsstr

‘Name’ of regressors in the current fork

spacestr

space label [1]

meanFDfloat

mean Jenkinson framewise displacement [2] CPAC.generate_motion_statistics.calculate_FD_J after preprocessing

relMeansRMSMotionfloat

“mean value of RMS motion” [3]

relMaxRMSMotionfloat

“maximum vaue of RMS motion” [3]

meanDVInitfloat

“mean DVARS” [3]

meanDVFinalfloat

“mean DVARS” [3]

nVolCensoredint

“total number of volume(s) censored [3]

nVolsRemovedint

number of volumes in derivative minus number of volumes in original functional scan

motionDVCorrInitfloat

“correlation of RMS and DVARS before regresion” [3]

motionDVCorrFinalfloat

“correlation of RMS and DVARS after regresion” [3]

coregDicefloat

“Coregsitration of Functional and T1w:[…] Dice index” [3]

coregJaccardfloat

“Coregsitration of Functional and T1w:[…] Jaccard index” [3]

coregCrossCorrfloat

“Coregsitration of Functional and T1w:[…] cross correlation” [3]

coregCoveragfloat

“Coregsitration of Functional and T1w:[…] Coverage index” [3]

normDicefloat

“Normalization of T1w/Functional to Template:[…] Dice index” [3]

normJaccardfloat

“Normalization of T1w/Functional to Template:[…] Jaccard index” [3]

normCrossCorrfloat

“Normalization of T1w/Functional to Template:[…] cross correlation” [3]

normCoveragefloat

“Normalization of T1w/Functional to Template:[…] Coverage index” [3]

CPAC.qc.xcp.dvcorr(dvars, fdj)[source]

Function to correlate DVARS and FD-J

CPAC.qc.xcp.generate_xcp_qc(sub, ses, task, run, desc, regressors, bold2t1w_mask, t1w_mask, bold2template_mask, template_mask, original_func, final_func, movement_parameters, dvars, censor_indices, framewise_displacement_jenkinson, dvars_after, template)[source]

Function to generate an RBC-style QC CSV

Parameters:

  • sub (str) – subject ID

  • ses (str) – session ID

  • task (str) – task ID

  • run (str or int) – run ID

  • desc (str) – description string

  • regressors (str) – ‘Name’ of regressors in fork

  • original_func (str) – path to original ‘bold’ image

  • final_bold (str) – path to ‘space-template_desc-preproc_bold’ image

  • bold2t1w_mask (str) – path to bold-to-T1w transform applied to space-bold_desc-brain_mask with space-T1w_desc-brain_mask reference

  • t1w_mask (str) – path to space-T1w_desc-brain_mask

  • bold2template_mask (str) – path to space-template_desc-bold_mask

  • template_mask (str) – path to space-template_desc-T1w_mask

  • movement_parameters (str) – path to movement parameters

  • dvars (str) – path to DVARS before motion correction

  • censor_indices (list) – list of indices of censored volumes

  • framewise_displacement_jenkinson (str) – path to framewise displacement (Jenkinson) before motion correction

  • dvars_after (str) – path to DVARS on final ‘bold’ image

  • template (str) – path to registration template

Returns:

path to space-template_desc-xcp_quality TSV

Return type:

str

CPAC.qc.xcp.get_bids_info(subject, scan, wf_name)[source]

Function to gather BIDS information from a strat_pool

Parameters:

  • subject (str) – subject ID

  • scan (str) – scan ID

  • wf_name (str) – workflow name

Returns:

  • subject (str) – subject ID

  • session (str) – session ID

  • task (str) – task ID

  • run (str or int) – run ID

Examples

>>> subject, session, task, run = get_bids_info(
...     subject='DavidBowman', scan='rest_acq-1_run-1',
...     wf_name='cpac_DavidBowman_3')
>>> subject
'DavidBowman'
>>> session
'3'
>>> task
'rest'
>>> run
'1'
>>> get_bids_info(subject='sub-colornest035', scan='rest_run-01',
...               wf_name='cpac_sub-colornest035_ses-1')
('colornest035', '1', 'rest', '01')

NodeBlockFunction: qc_xcp

CPAC.qc.xcp.qc_xcp(wf, cfg, strat_pool, pipe_num, opt=None)[source]
Parameters:
Returns:

References