Supported BIDS Suffixes

This page documents the BIDS suffixes currently supported by the default configuration of bids2nf (bids2nf.yaml). You can extend the configuration to support your own data structures.

Plain Sets¶

Plain sets define simple collections of files that do not require special grouping logic.

eeg¶

Electroencephalography

Electroencephalography recording data.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access json file:
  bids_channel['eeg']['json']
  // → eeg_cbm/sub-cbm001/eeg/sub-cbm001_task-protmap_eeg.json

  // Access edf file:
  bids_channel['eeg']['edf']
  // → eeg_cbm/sub-cbm001/eeg/sub-cbm001_task-protmap_eeg.edf

Example channel data structure

channels¶

Channels File

Channel information.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access tsv file:
  bids_channel['channels']['tsv']
  // → eeg_cbm/sub-cbm001/eeg/sub-cbm001_task-protmap_channels.tsv

Example channel data structure

dwi¶

Diffusion-weighted image

Diffusion-weighted imaging contrast (specialized T2 weighting).

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['dwi']['nii']
  // → ds-dwi/sub-01/dwi/sub-01_dwi.nii

  // Access json file:
  bids_channel['dwi']['json']
  // → ds-dwi/sub-01/dwi/sub-01_dwi.json

  // Access bval file:
  bids_channel['dwi']['bval']
  // → ds-dwi/sub-01/dwi/sub-01_dwi.bval

  // Access bvec file:
  bids_channel['dwi']['bvec']
  // → ds-dwi/sub-01/dwi/sub-01_dwi.bvec

Example channel data structure

sbref¶

Single-band reference image

Single-band reference for one or more multi-band dwi images.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['sbref']['nii']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-PA_sbref.nii.gz

  // Access json file:
  bids_channel['sbref']['json']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-PA_sbref.json

Example channel data structure

T1w¶

T1-weighted image

In arbitrary units (arbitrary). The contrast of these images is mainly determined by spatial variations in the longitudinal relaxation time of the imaged specimen. In spin-echo sequences this contrast is achieved at relatively short repetition and echo times. To achieve this weighting in gradient-echo images, again, short repetition and echo times are selected; however, at relatively large flip angles. Another common approach to increase T1 weighting in gradient-echo images is to add an inversion preparation block to the beginning of the imaging sequence (for example, TurboFLASH or MP-RAGE).

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['T1w']['nii']
  // → ds-dwi/sub-01/anat/sub-01_T1w.nii.gz

  // Access json file:
  bids_channel['T1w']['json']
  // → ds-dwi/sub-01/anat/sub-01_T1w.json

Example channel data structure

T2w¶

T2-weighted image

In arbitrary units (arbitrary). The contrast of these images is mainly determined by spatial variations in the (true) transverse relaxation time of the imaged specimen. In spin-echo sequences this contrast is achieved at relatively long repetition and echo times. Generally, gradient echo sequences are not the most suitable option for achieving T2 weighting, as their contrast natively depends on T2-star rather than on T2.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['T2w']['nii']
  // → ds-dwi4/sub-01/ses-005/anat/sub-01_ses-005_rec-norm_T2w.nii.gz

  // Access json file:
  bids_channel['T2w']['json']
  // → ds-dwi4/sub-01/ses-005/anat/sub-01_ses-005_rec-norm_T2w.json

Example channel data structure

T2starw¶

T2star weighted image

In arbitrary units (arbitrary). The contrast of these images is mainly determined by spatial variations in the (observed) transverse relaxation time of the imaged specimen. In spin-echo sequences, this effect is negated as the excitation is followed by an inversion pulse. The contrast of gradient-echo images natively depends on T2-star effects. However, for T2-star variation to dominate the image contrast, gradient-echo acquisitions are carried out at long repetition and echo times, and at small flip angles.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['T2starw']['nii']
  // → ds-dwi4/sub-01/ses-005/anat/sub-01_ses-005_bp-cspine_T2starw.nii.gz

  // Access json file:
  bids_channel['T2starw']['json']
  // → ds-dwi4/sub-01/ses-005/anat/sub-01_ses-005_bp-cspine_T2starw.json

Example channel data structure

asl¶

Arterial Spin Labeling

The complete ASL time series stored as a 4D NIfTI file in the original acquisition order, with possible volume types including: control, label, m0scan, deltam, cbf.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['asl']['nii']
  // → asl001/sub-Sub103/perf/sub-Sub103_asl.nii.gz

  // Access json file:
  bids_channel['asl']['json']
  // → asl001/sub-Sub103/perf/sub-Sub103_asl.json

Example channel data structure

aslcontext¶

Arterial Spin Labeling Context

A TSV file defining the image types for volumes in an associated ASL file.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access tsv file:
  bids_channel['aslcontext']['tsv']
  // → asl001/sub-Sub103/perf/sub-Sub103_aslcontext.tsv

Example channel data structure

m0scan¶

M0 image

The M0 image is a calibration image, used to estimate the equilibrium magnetization of blood.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['m0scan']['nii']
  // → asl002/sub-Sub103/perf/sub-Sub103_m0scan.nii.gz

  // Access json file:
  bids_channel['m0scan']['json']
  // → asl002/sub-Sub103/perf/sub-Sub103_m0scan.json

Example channel data structure

mrsref¶

MRS reference acquisition

An MRS acquisition collected to serve as a concentration reference for absolute quantification or as a calibration reference for preprocessing (for example, eddy-current correction).

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['mrsref']['nii']
  // → ds-mrs_fmrs/sub-01/mrs/sub-01_task-baseline_mrsref.nii.gz

  // Access json file:
  bids_channel['mrsref']['json']
  // → ds-mrs_fmrs/sub-01/mrs/sub-01_task-baseline_mrsref.json

Example channel data structure

Note

Input (MRS-MRF related) files (under the mrs directory) for this example dataset are:

sub-01_task-baseline_mrsref.nii.gz
sub-01_task-pain_mrsref.nii.gz

On the other hand, the T1w file is under the anat directory: sub-01_T1w.nii.gz.

By default, bids2nf is configured to loop over [subject, session, run, task] entities (see loop_over). Given that the T1w file does not have a task entity shared with either of these MRS-MRF files, Nextflow will emit it as a separate channel by default.

However, there may be a need to have all these files in the same channel. To do so, you can use the include_cross_modal option to include the T1w file in one of the suffixes (mrsref, in this case) to merge T1w channel (or some other suffix) onto it, as implemented in this example.

Alternatively you can customize loop_over to exclude the task entity and define named sets, assuming that the task values are known beforehand.

svs¶

Single-voxel spectroscopy

MRS acquisitions where the detected MR signal is spatially localized to a single volume.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['svs']['nii']
  // → ds-mrs_fmrs/sub-01/mrs/sub-01_task-pain_svs.nii.gz

  // Access json file:
  bids_channel['svs']['json']
  // → ds-mrs_fmrs/sub-01/mrs/sub-01_task-pain_svs.json

Example channel data structure

events¶

Events

Event timing information from a behavioral task.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access tsv file:
  bids_channel['events']['tsv']
  // → ds-mrs_fmrs/sub-01/mrs/sub-01_task-pain_events.tsv

Example channel data structure

UNIT1¶

Homogeneous (flat) T1-weighted MP2RAGE image

In arbitrary units (arbitrary). UNIT1 images are REQUIRED to use this suffix regardless of the method used to generate them. Note that although this image is T1-weighted, regions without MR signal will contain white salt-and-pepper noise that most segmentation algorithms will fail on. Therefore, it is important to dissociate it from T1w. Please see MP2RAGE specific notes in the qMRI appendix for further information.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['UNIT1']['nii']
  // → qmri_mp2rage/sub-1/anat/sub-1_UNIT1.nii

  // Access json file:
  bids_channel['UNIT1']['json']
  // → qmri_mp2rage/derivatives/pymp2rage/sub-1/anat/sub-1_UNIT1.json

Example channel data structure

epi¶

EPI

The phase-encoding polarity (PEpolar) technique combines two or more Spin Echo EPI scans with different phase encoding directions to estimate the underlying inhomogeneity/deformation map.

⌬ Hover to see the diagram legend

Example usage within a process

  // Access nii file:
  bids_channel['epi']['nii']
  // → ds-dwi3/sub-01/ses-005/fmap/sub-01_ses-005_dir-PA_epi.nii.gz

  // Access json file:
  bids_channel['epi']['json']
  // → ds-dwi3/sub-01/ses-005/fmap/sub-01_ses-005_dir-PA_epi.json

Example channel data structure

Named Sets¶

Named sets define specific collections of files with predefined names and properties.

MTS¶

Magnetization transfer saturation

This method is to calculate a semi-quantitative magnetization transfer saturation index map. The MTS method involves three sets of anatomical images that differ in terms of application of a magnetization transfer RF pulse (MTon or MToff) and flip angle (Helms et al. 2008).

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
T1w	T1-weighted image assuming flip-02 is the larger flip angle	flip: flip-02, mtransfer: mt-off
MTw	Magnetization transfer weighted image of the PD pair.	flip: flip-01, mtransfer: mt-on
PDw	Proton density weighted image assuming flip-01 is the lower flip angle	flip: flip-01, mtransfer: mt-off

Example usage within a process

  // Access PDw files:
  bids_channel['MTS']['PDw']['nii']
  // → qmri_mtsat/sub-01/anat/sub-01_flip-1_mt-off_MTS.nii.gz
  bids_channel['MTS']['PDw']['json']
  // → qmri_mtsat/sub-01/anat/sub-01_flip-1_mt-off_MTS.json

  // Access MTw files:
  bids_channel['MTS']['MTw']['nii']
  // → qmri_mtsat/sub-01/anat/sub-01_flip-1_mt-on_MTS.nii.gz
  bids_channel['MTS']['MTw']['json']
  // → qmri_mtsat/sub-01/anat/sub-01_flip-1_mt-on_MTS.json

  // Access T1w files:
  bids_channel['MTS']['T1w']['nii']
  // → qmri_mtsat/sub-01/anat/sub-01_flip-2_mt-off_MTS.nii.gz
  bids_channel['MTS']['T1w']['json']
  // → qmri_mtsat/sub-01/anat/sub-01_flip-2_mt-off_MTS.json

Example channel data structure

TB1TFL¶

The result of a Siemens tfl_b1_map product sequence. This sequence produces two images. The first image appears like an anatomical image and the second output is a scaled flip angle map.

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
anat	Anatomical-like image generated by the tfl_b1_map product sequence	acquisition: acq-anat
famp	scaled flip angle map	acquisition: acq-famp

Example usage within a process

  // Access anat files:
  bids_channel['TB1TFL']['anat']['nii']
  // → qmri_tb1tfl/sub-01/fmap/sub-01_acq-anat_TB1TFL.nii.gz
  bids_channel['TB1TFL']['anat']['json']
  // → qmri_tb1tfl/sub-01/fmap/sub-01_acq-anat_TB1TFL.json

  // Access famp files:
  bids_channel['TB1TFL']['famp']['nii']
  // → qmri_tb1tfl/sub-01/fmap/sub-01_acq-famp_TB1TFL.nii.gz
  bids_channel['TB1TFL']['famp']['json']
  // → qmri_tb1tfl/sub-01/fmap/sub-01_acq-famp_TB1TFL.json

Example channel data structure

TB1AFI¶

This method (Yarnykh 2007) calculates a B1⁺ map from two images acquired at interleaved (two) TRs with identical RF pulses using a steady-state sequence.

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
tr1	Image from the first interleaved TR of the AFI sequence	acquisition: acq-tr1
tr2	Image from the second interleaved TR of the AFI sequence	acquisition: acq-tr2

Example usage within a process

  // Access tr1 files:
  bids_channel['TB1AFI']['tr1']['nii']
  // → qmri_vfa/sub-01/fmap/sub-01_acq-tr1_TB1AFI.nii.gz
  bids_channel['TB1AFI']['tr1']['json']
  // → qmri_vfa/sub-01/fmap/sub-01_acq-tr1_TB1AFI.json

  // Access tr2 files:
  bids_channel['TB1AFI']['tr2']['nii']
  // → qmri_vfa/sub-01/fmap/sub-01_acq-tr2_TB1AFI.nii.gz
  bids_channel['TB1AFI']['tr2']['json']
  // → qmri_vfa/sub-01/fmap/sub-01_acq-tr2_TB1AFI.json

Example channel data structure

RB1COR¶

Low resolution images acquired by the body coil (in the gantry of the scanner) and the head coil using identical acquisition parameters to generate a combined sensitivity map as described in Papp et al. (2016).

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
bodyMTw	MTw B1- field from the body coil	acquisition: acq-bodyMTw
bodyT1w	T1w B1- field from the body coil	acquisition: acq-bodyT1w
bodyPDw	PDw B1- field from the body coil	acquisition: acq-bodyPDw
headMTw	MTw B1- field from the head coil	acquisition: acq-headMTw
headT1w	T1w B1- field from the head coil	acquisition: acq-headT1w
headPDw	PDw B1- field from the head coil	acquisition: acq-headPDw

Example usage within a process

  // Access bodyMTw files:
  bids_channel['RB1COR']['bodyMTw']['nii']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-bodyMTw_RB1COR.nii
  bids_channel['RB1COR']['bodyMTw']['json']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-bodyMTw_RB1COR.json

  // Access bodyPDw files:
  bids_channel['RB1COR']['bodyPDw']['nii']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-bodyPDw_RB1COR.nii
  bids_channel['RB1COR']['bodyPDw']['json']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-bodyPDw_RB1COR.json

  // Access bodyT1w files:
  bids_channel['RB1COR']['bodyT1w']['nii']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-bodyT1w_RB1COR.nii
  bids_channel['RB1COR']['bodyT1w']['json']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-bodyT1w_RB1COR.json

  // Access headMTw files:
  bids_channel['RB1COR']['headMTw']['nii']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-headMTw_RB1COR.nii
  bids_channel['RB1COR']['headMTw']['json']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-headMTw_RB1COR.json

  // Access headPDw files:
  bids_channel['RB1COR']['headPDw']['nii']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-headPDw_RB1COR.nii
  bids_channel['RB1COR']['headPDw']['json']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-headPDw_RB1COR.json

  // Access headT1w files:
  bids_channel['RB1COR']['headT1w']['nii']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-headT1w_RB1COR.nii
  bids_channel['RB1COR']['headT1w']['json']
  // → qmri_mpm/sub-01/fmap/sub-01_acq-headT1w_RB1COR.json

Example channel data structure

Sequential Sets¶

Sequential sets define collections of files organized by BIDS entities.

VFA¶

Variable flip angle

The VFA method involves at least two spoiled gradient echo (SPGR) of steady-state free precession (SSFP) images acquired at different flip angles. Depending on the provided metadata fields and the sequence type, data may be eligible for DESPOT1, DESPOT2 and their variants (Deoni et al. 2005).

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['VFA']['nii'].size()  // → 2
  // Access first item
  bids_channel['VFA']['nii'][0]
  // → qmri_vfa/sub-01/anat/sub-01_flip-1_VFA.nii.gz
  bids_channel['VFA']['json'][0]
  // → qmri_vfa/sub-01/anat/sub-01_flip-1_VFA.json

  // Access second item
  bids_channel['VFA']['nii'][1]
  // → qmri_vfa/sub-01/anat/sub-01_flip-2_VFA.nii.gz
  bids_channel['VFA']['json'][1]
  // → qmri_vfa/sub-01/anat/sub-01_flip-2_VFA.json

Example channel data structure

IRT1¶

Inversion recovery T1 mapping

The IRT1 method involves multiple inversion recovery spin-echo images acquired at different inversion times (Barral et al. 2010).

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['IRT1']['nii'].size()  // → 4
  // Access first item
  bids_channel['IRT1']['nii'][0]
  // → qmri_irt1/sub-01/anat/sub-01_inv-01_IRT1.nii.gz
  bids_channel['IRT1']['json'][0]
  // → qmri_irt1/sub-01/anat/sub-01_inv-01_IRT1.json

  // Access second item
  bids_channel['IRT1']['nii'][1]
  // → qmri_irt1/sub-01/anat/sub-01_inv-02_IRT1.nii.gz
  bids_channel['IRT1']['json'][1]
  // → qmri_irt1/sub-01/anat/sub-01_inv-02_IRT1.json

Example channel data structure

TB1DAM¶

The double-angle B1⁺ method (Insko and Bolinger 1993) is based on the calculation of the actual angles from signal ratios, collected by two acquisitions at different nominal excitation flip angles. Common sequence types for this application include spin echo and echo planar imaging.

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['TB1DAM']['nii'].size()  // → 2
  // Access first item
  bids_channel['TB1DAM']['nii'][0]
  // → qmri_mtsat/sub-01/fmap/sub-01_flip-1_TB1DAM.nii.gz
  bids_channel['TB1DAM']['json'][0]
  // → qmri_mtsat/sub-01/fmap/sub-01_flip-1_TB1DAM.json

  // Access second item
  bids_channel['TB1DAM']['nii'][1]
  // → qmri_mtsat/sub-01/fmap/sub-01_flip-2_TB1DAM.nii.gz
  bids_channel['TB1DAM']['json'][1]
  // → qmri_mtsat/sub-01/fmap/sub-01_flip-2_TB1DAM.json

Example channel data structure

MEGRE¶

Multi-echo Gradient Recalled Echo

Anatomical gradient echo images acquired at different echo times. Please note that this suffix is not intended for the logical grouping of images acquired using an Echo Planar Imaging (EPI) readout.

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['MEGRE']['nii'].size()  // → 8
  // Access first item
  bids_channel['MEGRE']['nii'][0]
  // → qmri_megre/sub-01/anat/sub-01_echo-01_MEGRE.nii.gz
  bids_channel['MEGRE']['json'][0]
  // → qmri_megre/sub-01/anat/sub-01_echo-01_MEGRE.json

  // Access second item
  bids_channel['MEGRE']['nii'][1]
  // → qmri_megre/sub-01/anat/sub-01_echo-02_MEGRE.nii.gz
  bids_channel['MEGRE']['json'][1]
  // → qmri_megre/sub-01/anat/sub-01_echo-02_MEGRE.json

Example channel data structure

MESE¶

Multi-echo Spin Echo

The MESE method involves multiple spin echo images acquired at different echo times and is primarily used for T2 mapping. Please note that this suffix is not intended for the logical grouping of images acquired using an Echo Planar Imaging (EPI) readout.

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['MESE']['nii'].size()  // → 32
  // Access first item
  bids_channel['MESE']['nii'][0]
  // → qmri_mese/sub-01/anat/sub-01_echo-01_MESE.nii.gz
  bids_channel['MESE']['json'][0]
  // → qmri_mese/sub-01/anat/sub-01_echo-01_MESE.json

  // Access second item
  bids_channel['MESE']['nii'][1]
  // → qmri_mese/sub-01/anat/sub-01_echo-02_MESE.nii.gz
  bids_channel['MESE']['json'][1]
  // → qmri_mese/sub-01/anat/sub-01_echo-02_MESE.json

Example channel data structure

TB1SRGE¶

Saturation-prepared with 2 rapid gradient echoes (SA2RAGE) uses a ratio of two saturation recovery images with different time delays, and a simulated look-up table to estimate B1+ (Eggenschwiler et al. 2011). This sequence can also be used in conjunction with MP2RAGE T1 mapping to iteratively improve B1+ and T1 map estimation (Marques & Gruetter 2013).

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['TB1SRGE']['nii'].size()  // → 2
  // Access first item
  bids_channel['TB1SRGE']['nii'][0]
  // → ['qmri_sa2rage/sub-01/fmap/sub-01_flip-1_inv-1_TB1SRGE.nii.gz']
  bids_channel['TB1SRGE']['json'][0]
  // → ['qmri_sa2rage/sub-01/fmap/sub-01_flip-1_inv-1_TB1SRGE.json']

  // Access second item
  bids_channel['TB1SRGE']['nii'][1]
  // → ['qmri_sa2rage/sub-01/fmap/sub-01_flip-2_inv-2_TB1SRGE.nii.gz']
  bids_channel['TB1SRGE']['json'][1]
  // → ['qmri_sa2rage/sub-01/fmap/sub-01_flip-2_inv-2_TB1SRGE.json']

Example channel data structure

TB1EPI¶

This B1⁺ mapping method (Jiru and Klose 2006) is based on two EPI readouts to acquire spin echo (SE) and stimulated echo (STE) images at multiple flip angles in one sequence, used in the calculation of deviations from the nominal flip angle.

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['TB1EPI']['nii'].size()  // → 2
  // Access first item
  bids_channel['TB1EPI']['nii'][0]
  // → ['qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-01_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-02_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-03_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-04_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-05_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-06_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-07_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-08_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-09_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-10_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-11_TB1EPI.nii']
  bids_channel['TB1EPI']['json'][0]
  // → ['qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-01_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-02_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-03_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-04_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-05_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-06_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-07_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-08_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-09_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-10_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-1_flip-11_TB1EPI.json']

  // Access second item
  bids_channel['TB1EPI']['nii'][1]
  // → ['qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-01_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-02_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-03_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-04_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-05_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-06_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-07_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-08_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-09_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-10_TB1EPI.nii', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-11_TB1EPI.nii']
  bids_channel['TB1EPI']['json'][1]
  // → ['qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-01_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-02_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-03_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-04_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-05_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-06_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-07_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-08_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-09_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-10_TB1EPI.json', 'qmri_mpm/sub-01/fmap/sub-01_echo-2_flip-11_TB1EPI.json']

Example channel data structure

MP2RAGE¶

Magnetization Prepared Two Gradient Echoes

The MP2RAGE method is a special protocol that collects several images at different flip angles and inversion times to create a parametric T1map by combining the magnitude and phase images (Marques et al. 2010).

⌬ Hover to see the diagram legend

Example usage within a process

  // Get number of items in sequential set
  bids_channel['MP2RAGE']['nii'].size()
  // Access first item
  bids_channel['MP2RAGE']['nii'][0]
  bids_channel['MP2RAGE']['json'][0]

Mixed Sets¶

Mixed sets combine named groups with sequential organization within each group.

MPM¶

Multi-parametric Mapping

The MPM approaches (a.k.a hMRI) involves the acquisition of highly-similar anatomical images that differ in terms of application of a magnetization transfer RF pulse (MTon or MToff), flip angle and (optionally) echo time and magnitue/phase parts (Weiskopf et al. 2013). See here for suggested MPM acquisition protocols.

⌬ Hover to see the diagram legend

Named Group	Description	Entity-based mapping
MTw	Magnetization transfer weighted images	acquisition: acq-MTw, flip: flip-1, mtransfer: mt-on
PDw	Proton density weighted images	acquisition: acq-PDw, flip: flip-1, mtransfer: mt-off
T1w	T1-weighted images	acquisition: acq-T1w, flip: flip-2, mtransfer: mt-off

Required groups: None

Example usage within a process

  // Access MTw group:
  bids_channel['MPM']['MTw']['nii'].size()  // → 6
  bids_channel['MPM']['MTw']['nii'][0]
  // → qmri_mpm/sub-01/anat/sub-01_acq-MTw_echo-1_flip-1_mt-on_MPM.nii
  bids_channel['MPM']['MTw']['json'][0]
  // → qmri_mpm/sub-01/anat/sub-01_acq-MTw_echo-1_flip-1_mt-on_MPM.json

  // Access second echo in MTw:
  bids_channel['MPM']['MTw']['nii'][1]
  // → qmri_mpm/sub-01/anat/sub-01_acq-MTw_echo-2_flip-1_mt-on_MPM.nii
  bids_channel['MPM']['MTw']['json'][1]
  // → qmri_mpm/sub-01/anat/sub-01_acq-MTw_echo-2_flip-1_mt-on_MPM.json

  // Access PDw group:
  bids_channel['MPM']['PDw']['nii'].size()  // → 8
  bids_channel['MPM']['PDw']['nii'][0]
  // → qmri_mpm/sub-01/anat/sub-01_acq-PDw_echo-1_flip-1_mt-off_MPM.nii
  bids_channel['MPM']['PDw']['json'][0]
  // → qmri_mpm/sub-01/anat/sub-01_acq-PDw_echo-1_flip-1_mt-off_MPM.json

  // Access second echo in PDw:
  bids_channel['MPM']['PDw']['nii'][1]
  // → qmri_mpm/sub-01/anat/sub-01_acq-PDw_echo-2_flip-1_mt-off_MPM.nii
  bids_channel['MPM']['PDw']['json'][1]
  // → qmri_mpm/sub-01/anat/sub-01_acq-PDw_echo-2_flip-1_mt-off_MPM.json

  // Access T1w group:
  bids_channel['MPM']['T1w']['nii'].size()  // → 8
  bids_channel['MPM']['T1w']['nii'][0]
  // → qmri_mpm/sub-01/anat/sub-01_acq-T1w_echo-1_flip-2_mt-off_MPM.nii
  bids_channel['MPM']['T1w']['json'][0]
  // → qmri_mpm/sub-01/anat/sub-01_acq-T1w_echo-1_flip-2_mt-off_MPM.json

  // Access second echo in T1w:
  bids_channel['MPM']['T1w']['nii'][1]
  // → qmri_mpm/sub-01/anat/sub-01_acq-T1w_echo-2_flip-2_mt-off_MPM.nii
  bids_channel['MPM']['T1w']['json'][1]
  // → qmri_mpm/sub-01/anat/sub-01_acq-T1w_echo-2_flip-2_mt-off_MPM.json

Example channel data structure

Special Sets¶

Special sets are special cases that do not fit into the other categories.

dwi_fullreverse¶

Additional grouping logic for dwi

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
ap	No description	direction: dir-AP
pa	No description	direction: dir-PA

Example usage within a process

  // Access ap files:
  bids_channel['dwi_fullreverse']['ap']['nii']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-AP_dwi.nii.gz
  bids_channel['dwi_fullreverse']['ap']['json']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-AP_dwi.json

  // Access pa files:
  bids_channel['dwi_fullreverse']['pa']['nii']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-PA_dwi.nii.gz
  bids_channel['dwi_fullreverse']['pa']['json']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-PA_dwi.json

Example channel data structure

sbref_fullreverse¶

Additional grouping logic for sbref

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
ap	No description	direction: dir-AP
pa	No description	direction: dir-PA

Example usage within a process

  // Access ap files:
  bids_channel['sbref_fullreverse']['ap']['nii']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-AP_sbref.nii.gz
  bids_channel['sbref_fullreverse']['ap']['json']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-AP_sbref.json

  // Access pa files:
  bids_channel['sbref_fullreverse']['pa']['nii']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-PA_sbref.nii.gz
  bids_channel['sbref_fullreverse']['pa']['json']
  // → ds-dwi4/sub-01/ses-005/dwi/sub-01_ses-005_dir-PA_sbref.json

Example channel data structure

epi_fullreverse¶

Additional grouping logic for epi

⌬ Hover to see the diagram legend

Key	Description	Entity-based mapping
ap	No description	direction: dir-AP
pa	No description	direction: dir-PA

Example usage within a process

  bids_channel['epi_fullreverse']['ap']['nii']
  bids_channel['epi_fullreverse']['ap']['json']
  bids_channel['epi_fullreverse']['pa']['nii']
  bids_channel['epi_fullreverse']['pa']['json']

Example channel data structure

MP2RAGE_multiecho¶

Additional grouping logic for MP2RAGE

⌬ Hover to see the diagram legend

Example usage within a process

  // Multiple entities organized by: inversion, echo
  // First dimension: inversion, Second dimension: echo
  // Get size of first dimension (inversion)
  bids_channel['MP2RAGE_multiecho']['nii'].size()
  // Get size of second dimension (echo) for first inversion
  bids_channel['MP2RAGE_multiecho']['nii'][0].size()
  // Access first item
  bids_channel['MP2RAGE_multiecho']['nii'][0][0]
  bids_channel['MP2RAGE_multiecho']['json'][0][0]

This documentation is automatically generated from bids2nf.yaml.

References¶

Helms, G., Dathe, H., Kallenberg, K., & Dechent, P. (2008). High‐resolution maps of magnetization transfer with inherent correction for RF inhomogeneity and T1 relaxation obtained from 3D FLASH MRI. Magnetic Resonance in Medicine, 60(6), 1396–1407. 10.1002/mrm.21732
Yarnykh, V. L. (2006). Actual flip‐angle imaging in the pulsed steady state: A method for rapid three‐dimensional mapping of the transmitted radiofrequency field. Magnetic Resonance in Medicine, 57(1), 192–200. 10.1002/mrm.21120
Papp, D., Callaghan, M. F., Meyer, H., Buckley, C., & Weiskopf, N. (2015). Correction of inter‐scan motion artifacts in quantitative R1 mapping by accounting for receive coil sensitivity effects. Magnetic Resonance in Medicine, 76(5), 1478–1485. 10.1002/mrm.26058
Deoni, S. C. L., Peters, T. M., & Rutt, B. K. (2004). High‐resolution T1 and T2 mapping of the brain in a clinically acceptable time with DESPOT1 and DESPOT2. Magnetic Resonance in Medicine, 53(1), 237–241. 10.1002/mrm.20314
Barral, J. K., Gudmundson, E., Stikov, N., Etezadi‐Amoli, M., Stoica, P., & Nishimura, D. G. (2010). A robust methodology for in vivo T1 mapping. Magnetic Resonance in Medicine, 64(4), 1057–1067. 10.1002/mrm.22497
Insko, E. K., & Bolinger, L. (1993). Mapping of the Radiofrequency Field. Journal of Magnetic Resonance, Series A, 103(1), 82–85. 10.1006/jmra.1993.1133
Eggenschwiler, F., Kober, T., Magill, A. W., Gruetter, R., & Marques, J. P. (2011). SA2RAGE: A new sequence for fast B1+‐mapping. Magnetic Resonance in Medicine, 67(6), 1609–1619. 10.1002/mrm.23145
Marques, J. P., & Gruetter, R. (2013). New Developments and Applications of the MP2RAGE Sequence - Focusing the Contrast and High Spatial Resolution R1 Mapping. PLoS ONE, 8(7), e69294. 10.1371/journal.pone.0069294
Jiru, F., & Klose, U. (2006). Fast 3D radiofrequency field mapping using echo‐planar imaging. Magnetic Resonance in Medicine, 56(6), 1375–1379. 10.1002/mrm.21083
Marques, J. P., Kober, T., Krueger, G., van der Zwaag, W., Van de Moortele, P.-F., & Gruetter, R. (2010). MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. NeuroImage, 49(2), 1271–1281. 10.1016/j.neuroimage.2009.10.002
Weiskopf, N., Suckling, J., Williams, G., Correia, M. M., Inkster, B., Tait, R., Ooi, C., Bullmore, E. T., & Lutti, A. (2013). Quantitative multi-parameter mapping of R1, PD*, MT, and R2* at 3T: a multi-center validation. Frontiers in Neuroscience, 7. 10.3389/fnins.2013.00095