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The Filter Cart provides a powerful way to query and access data for which you may be interested.  

A few points related to the filter cart are important to understand with the NDA Query/Filter implementation: 

First, the filter cart is populated asyncronously.  So, when you run a query, it may take a moment to populate but this will happen in the background so you can define other queries during this time.  

When you are adding your first filter, all data associated with your query will be added to the filter cart (whether it be a collection, a concept, a study, a data structure/elment or subjects). Not all data structures or collections will necessarily be displayed.  For example, if you select the NDA imaging structure image03, and further restrict that query to scan_type fMRI, only fMRI images will appear and only the image03 structure will be shown.  To see other data structures, select "Find All Subject Data" which will query all data for those subjects. When a secord or third filter is applied, an AND condition is used.  A subject must exist in all filters.  If the subject does not appear in any one filter, that subjects data will not be included in your filter cart. If that happens, clear your filter cart, and start over.  

It is best to package more data than you need and access those data using other tools, independent of the NDA (e.g. miNDAR snapshot), to limit the data selected.  If you have any questions on data access, are interested in using avaialble web services, or need help accessing data, please contact us for assistance.  

Frequently Asked Questions

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Magnetic Resonance Image Quality Metrics

0 Shared Subjects

N/A
Neurosignal Recordings
Evaluated Data
04/12/2019
mriqm01
04/12/2019
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01
Query Element Name Data Type Size Required Description Value Range Notes Aliases
subjectkey GUID Required The NDAR Global Unique Identifier (GUID) for research subject NDAR*
src_subject_id String 20 Required Subject ID how it's defined in lab/project subject_id
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY Required field
interview_age Integer Required Age in months at the time of the interview/test/sampling/imaging. 0 :: 1260 Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month.
sex String 20 Required Sex of the subject M;F M = Male; F = Female gender
scan_type String 50 Required Type of Scan MR diffusion; fMRI; MR structural (MPRAGE); MR structural (T1); MR structural (PD); MR structural (FSPGR); MR structural (FISP); MR structural (T2); PET; ASL; microscopy; MR structural (PD, T2); MR structural (B0 map); MR structural (B1 map); single-shell DTI; multi-shell DTI; Field Map; X-Ray; static magnetic field B0; pCASL: ASL; MR: T2star; MR: FLAIR; Localizer scan; MR structural (FLASH); MR structural (MP2RAGE); MR structural (TSE); MR structural (T1, T2); 2D gradient echo; MR structural (MPnRAGE)
t1_cjv Float Conditional coefficient of joint variation (CJV): The cjv of GM and WM was proposed as objective function by [Ganzetti2016] for the optimization of INU correction algorithms. Higher values are related to the presence of heavy head motion and large INU artifacts. Lower values are better.
t1_cnr Float Conditional contrast-to-noise ratio (CNR): The cnr [Magnota2006], is an extension of the SNR calculation to evaluate how separated the tissue distributions of GM and WM are. Higher values indicate better quality.
t1_efc Float Conditional The EFC [Atkinson1997] uses the Shannon entropy of voxel intensities as an indication of ghosting and blurring induced by head motion. Lower values are better. The original equation is normalized by the maximum entropy, so that the EFC can be compared across images with different dimensions.
t1_fber Float Conditional The FBER [Shehzad2015], defined as the mean energy of image values within the head relative to outside the head [QAP-measures]. Higher values are better.
t1_fwhm_avg Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t1_fwhm_x Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t1_fwhm_y Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t1_fwhm_z Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t1_icvs_csf Float Conditional The ICV fractions of CSF, GM and WM. They should move within a normative range.
t1_icvs_gm Float Conditional The ICV fractions of CSF, GM and WM. They should move within a normative range.
t1_icvs_wm Float Conditional The ICV fractions of CSF, GM and WM. They should move within a normative range.
t1_inu_med Float Conditional summary statistics (max, min and median) of the INU field as extracted by the N4ITK algorithm [Tustison2010]. Values closer to 1.0 are better.
t1_inu_range Float Conditional summary statistics (max, min and median) of the INU field as extracted by the N4ITK algorithm [Tustison2010]. Values closer to 1.0 are better.
t1_qi_1 Float Conditional Detect artifacts in the image using the method described in [Mortamet2009]. The QI1 is the proportion of voxels with intensity corrupted by artifacts normalized by the number of voxels in the background. Lower values are better.
t1_qi_2 Float Conditional Mortamet's quality index 2 (QI2) is a calculation of the goodness-of-fit of a chi-2 distribution on the air mask, once the artifactual intensities detected for computing the QI1 index have been removed [Mortamet2009].
t1_rpve_csf Float Conditional the rPVe of CSF, GM and WM. Lower values are better.
t1_rpve_gm Float Conditional the rPVe of CSF, GM and WM. Lower values are better.
t1_rpve_wm Float Conditional the rPVe of CSF, GM and WM. Lower values are better.
t1_size_x Integer Conditional extent in number of voxels
t1_size_y Integer Conditional extent in number of voxels
t1_size_z Integer Conditional extent in number of voxels
t1_snr_csf Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t1_snr_gm Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t1_snr_total Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t1_snr_wm Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t1_snrd_csf Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t1_snrd_gm Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t1_snrd_total Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t1_snrd_wm Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t1_spacing_x Float Conditional Distance in mm betwen centers of adjacent voxels in x direction
t1_spacing_y Float Conditional Distance in mm betwen centers of adjacent voxels in y direction
t1_spacing_z Float Conditional Distance in mm betwen centers of adjacent voxels in z direction
t1_summary_bg_k Float Conditional background kurtosis
t1_summary_bg_mad Float Conditional background median absolute deviation
t1_summary_bg_mean Float Conditional background mean
t1_summary_bg_median Float Conditional background median absolute deviation
t1_summary_bg_n Float Conditional background count of voxels
t1_summary_bg_p05 Float Conditional background 5th percentile
t1_summary_bg_p95 Float Conditional background 95th percentile
t1_summary_bg_stdv Float Conditional background standard deviation
t1_summary_csf_k Float Conditional cerebrospinal fluid kurtosis
t1_summary_csf_mad Float Conditional cerebrospinal fluid median absolute deviation
t1_summary_csf_mean Float Conditional cerebrospinal fluid mean
t1_summary_csf_median Float Conditional cerebrospinal fluid median absolute deviation
t1_summary_csf_n Float Conditional cerebrospinal fluid count of voxels
t1_summary_csf_p05 Float Conditional cerebrospinal fluid 5th percentile
t1_summary_csf_p95 Float Conditional cerebrospinal fluid 95th percentile
t1_summary_csf_stdv Float Conditional cerebrospinal fluid standard deviation
t1_summary_gm_k Float Conditional grey matter kurtosis
t1_summary_gm_mad Float Conditional grey matter median absolute deviation
t1_summary_gm_mean Float Conditional grey matter mean
t1_summary_gm_median Float Conditional grey matter median absolute deviation
t1_summary_gm_n Float Conditional grey matter count of voxels
t1_summary_gm_p05 Float Conditional grey matter 5th percentile
t1_summary_gm_p95 Float Conditional grey matter 95th percentile
t1_summary_gm_stdv Float Conditional grey matter standard deviation
t1_summary_wm_k Float Conditional white matter kurtosis
t1_summary_wm_mad Float Conditional white matter median absolute deviation
t1_summary_wm_mean Float Conditional white matter mean
t1_summary_wm_median Float Conditional white matter median absolute deviation
t1_summary_wm_n Float Conditional white matter count of voxels
t1_summary_wm_p05 Float Conditional white matter 5th percentile
t1_summary_wm_p95 Float Conditional white matter 95th percentile
t1_summary_wm_stdv Float Conditional white matter standard deviation
t1_tpm_overlap_csf Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t1_tpm_overlap_gm Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t1_tpm_overlap_wm Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t1_wm2max Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t2_cjv Float Conditional coefficient of joint variation (CJV): The cjv of GM and WM was proposed as objective function by [Ganzetti2016] for the optimization of INU correction algorithms. Higher values are related to the presence of heavy head motion and large INU artifacts. Lower values are better.
t2_cnr Float Conditional contrast-to-noise ratio (CNR): The cnr [Magnota2006], is an extension of the SNR calculation to evaluate how separated the tissue distributions of GM and WM are. Higher values indicate better quality.
t2_efc Float Conditional The EFC [Atkinson1997] uses the Shannon entropy of voxel intensities as an indication of ghosting and blurring induced by head motion. Lower values are better. The original equation is normalized by the maximum entropy, so that the EFC can be compared across images with different dimensions.
t2_fber Float Conditional The FBER [Shehzad2015], defined as the mean energy of image values within the head relative to outside the head [QAP-measures]. Higher values are better.
t2_fwhm_avg Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t2_fwhm_x Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t2_fwhm_y Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t2_fwhm_z Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
t2_icvs_csf Float Conditional The ICV fractions of CSF, GM and WM. They should move within a normative range.
t2_icvs_gm Float Conditional The ICV fractions of CSF, GM and WM. They should move within a normative range.
t2_icvs_wm Float Conditional The ICV fractions of CSF, GM and WM. They should move within a normative range.
t2_inu_med Float Conditional summary statistics (max, min and median) of the INU field as extracted by the N4ITK algorithm [Tustison2010]. Values closer to 1.0 are better.
t2_inu_range Float Conditional summary statistics (max, min and median) of the INU field as extracted by the N4ITK algorithm [Tustison2010]. Values closer to 1.0 are better.
t2_qi_1 Float Conditional Detect artifacts in the image using the method described in [Mortamet2009]. The QI1 is the proportion of voxels with intensity corrupted by artifacts normalized by the number of voxels in the background. Lower values are better.
t2_qi_2 Float Conditional Mortamet's quality index 2 (QI2) is a calculation of the goodness-of-fit of a chi-2 distribution on the air mask, once the artifactual intensities detected for computing the QI1 index have been removed [Mortamet2009].
t2_rpve_csf Float Conditional the rPVe of CSF, GM and WM. Lower values are better.
t2_rpve_gm Float Conditional the rPVe of CSF, GM and WM. Lower values are better.
t2_rpve_wm Float Conditional the rPVe of CSF, GM and WM. Lower values are better.
t2_size_x Integer Conditional extent in number of voxels
t2_size_y Integer Conditional extent in number of voxels
t2_size_z Integer Conditional extent in number of voxels
t2_snr_csf Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t2_snr_gm Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t2_snr_total Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t2_snr_wm Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
t2_snrd_csf Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t2_snrd_gm Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t2_snrd_total Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t2_snrd_wm Float Conditional Dietrich's SNR (SNRd) as proposed by [Dietrich2007], using the air background as reference.
t2_spacing_x Float Conditional Distance in mm betwen centers of adjacent voxels in x direction
t2_spacing_y Float Conditional Distance in mm betwen centers of adjacent voxels in y direction
t2_spacing_z Float Conditional Distance in mm betwen centers of adjacent voxels in z direction
t2_summary_bg_k Float Conditional background kurtosis
t2_summary_bg_mad Float Conditional background median absolute deviation
t2_summary_bg_mean Float Conditional background mean
t2_summary_bg_median Float Conditional background median absolute deviation
t2_summary_bg_n Float Conditional background count of voxels
t2_summary_bg_p05 Float Conditional background 5th percentile
t2_summary_bg_p95 Float Conditional background 95th percentile
t2_summary_bg_stdv Float Conditional background standard deviation
t2_summary_csf_k Float Conditional cerebrospinal fluid kurtosis
t2_summary_csf_mad Float Conditional cerebrospinal fluid median absolute deviation
t2_summary_csf_mean Float Conditional cerebrospinal fluid mean
t2_summary_csf_median Float Conditional cerebrospinal fluid median absolute deviation
t2_summary_csf_n Float Conditional cerebrospinal fluid count of voxels
t2_summary_csf_p05 Float Conditional cerebrospinal fluid 5th percentile
t2_summary_csf_p95 Float Conditional cerebrospinal fluid 95th percentile
t2_summary_csf_stdv Float Conditional cerebrospinal fluid standard deviation
t2_summary_gm_k Float Conditional grey matter kurtosis
t2_summary_gm_mad Float Conditional grey matter median absolute deviation
t2_summary_gm_mean Float Conditional grey matter mean
t2_summary_gm_median Float Conditional grey matter median absolute deviation
t2_summary_gm_n Float Conditional grey matter count of voxels
t2_summary_gm_p05 Float Conditional grey matter 5th percentile
t2_summary_gm_p95 Float Conditional grey matter 95th percentile
t2_summary_gm_stdv Float Conditional grey matter standard deviation
t2_summary_wm_k Float Conditional white matter kurtosis
t2_summary_wm_mad Float Conditional white matter median absolute deviation
t2_summary_wm_mean Float Conditional white matter mean
t2_summary_wm_median Float Conditional white matter median absolute deviation
t2_summary_wm_n Float Conditional white matter count of voxels
t2_summary_wm_p05 Float Conditional white matter 5th percentile
t2_summary_wm_p95 Float Conditional white matter 95th percentile
t2_summary_wm_stdv Float Conditional white matter standard deviation
t2_tpm_overlap_csf Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t2_tpm_overlap_gm Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t2_tpm_overlap_wm Float Conditional The overlap of the TPMs estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template.
t2_wm2max Float Conditional The white-matter to maximum intensity ratio is the median intensity within the WM mask over the 95% percentile of the full intensity distribution, that captures the existence of long tails due to hyper-intensity of the carotid vessels and fat. Values should be around the interval [0.6, 0.8].
bold_dummy_trs Integer Conditional Number of volumes (“dummy scans”) discarded by the scanner (as opposed to those discarded by the user post hoc) before saving the imaging file. For example, a sequence that automatically discards the first 4 volumes before saving would have this field as 4. A sequence that doesn’t discard dummy scans would have this set to 0.
bold_dvars_nstd Float Conditional D referring to temporal derivative of timecourses, VARS referring to RMS variance over voxels ([Power2012] dvars_nstd) indexes the rate of change of BOLD signal across the entire brain at each frame of data. DVARS is calculated with nipype after motion correction
bold_dvars_std Float Conditional D referring to temporal derivative of timecourses, VARS referring to RMS variance over voxels ([Power2012] dvars_nstd) indexes the rate of change of BOLD signal across the entire brain at each frame of data. DVARS is calculated with nipype after motion correction
bold_dvars_vstd Float Conditional D referring to temporal derivative of timecourses, VARS referring to RMS variance over voxels ([Power2012] dvars_nstd) indexes the rate of change of BOLD signal across the entire brain at each frame of data. DVARS is calculated with nipype after motion correction
bold_efc Float Conditional The EFC [Atkinson1997] uses the Shannon entropy of voxel intensities as an indication of ghosting and blurring induced by head motion. Lower values are better. The original equation is normalized by the maximum entropy, so that the EFC can be compared across images with different dimensions.
bold_fber Float Conditional The FBER [Shehzad2015], defined as the mean energy of image values within the head relative to outside the head [QAP-measures]. Higher values are better.
bold_fd_mean Float Conditional expresses instantaneous head-motion. MRIQC reports the average FD, labeled as fd_mean. Rotational displacements are calculated as the displacement on the surface of a sphere of radius 50 mm. Along with the base framewise displacement, MRIQC reports the number of timepoints above FD threshold (fd_num), and the percent of FDs above the FD threshold w.r.t. the full timeseries (fd_perc). In both cases, the threshold is set at 0.20mm. [Power2012]:
bold_fd_num Float Conditional expresses instantaneous head-motion. MRIQC reports the average FD, labeled as fd_mean. Rotational displacements are calculated as the displacement on the surface of a sphere of radius 50 mm. Along with the base framewise displacement, MRIQC reports the number of timepoints above FD threshold (fd_num), and the percent of FDs above the FD threshold w.r.t. the full timeseries (fd_perc). In both cases, the threshold is set at 0.20mm. [Power2012]:
bold_fd_perc Float Conditional expresses instantaneous head-motion. MRIQC reports the average FD, labeled as fd_mean. Rotational displacements are calculated as the displacement on the surface of a sphere of radius 50 mm. Along with the base framewise displacement, MRIQC reports the number of timepoints above FD threshold (fd_num), and the percent of FDs above the FD threshold w.r.t. the full timeseries (fd_perc). In both cases, the threshold is set at 0.20mm. [Power2012]:
bold_fwhm_avg Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
bold_fwhm_x Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
bold_fwhm_y Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
bold_fwhm_z Float Conditional The FWHM of the spatial distribution of the image intensity values in units of voxels [Forman1995]. Lower values are better. Uses the gaussian width estimator filter implemented in AFNI's 3dFWHMx
bold_gcor Float Conditional Global Correlation (gcor) calculates an optimized summary of time-series correlation as in [Saad2013] using AFNI's @compute_gcor
bold_gsr_x Float Conditional Ghost to Signal Ratio (gsr(), labeled in the reports as gsr_x and gsr_y): along the two possible phase-encoding axes x, y
bold_gsr_y Float Conditional Ghost to Signal Ratio (gsr(), labeled in the reports as gsr_x and gsr_y): along the two possible phase-encoding axes x, y
bold_prov_set_fd_thresh Float Conditional Provisional setting of framewise displacement threshold
bold_size_t Float Conditional number of time points
bold_size_x Float Conditional extent in number of voxels
bold_size_y Float Conditional extent in number of voxels
bold_size_z Float Conditional extent in number of voxels
bold_snr Float Conditional signal-to-noise ratio (SNR): calculated within the tissue mask.
bold_spacing_tr Float Conditional Length of time between the begining of adjacent trs in s
bold_spacing_x Float Conditional Distance in mm betwen centers of adjacent voxels in x direction
bold_spacing_y Float Conditional Distance in mm betwen centers of adjacent voxels in y direction
bold_spacing_z Float Conditional Distance in mm betwen centers of adjacent voxels in z direction
bold_summary_bg_k Float Conditional background kurtosis
bold_summary_bg_mad Float Conditional background median absolute deviation
bold_summary_bg_mean Float Conditional background mean
bold_summary_bg_median Float Conditional background median absolute deviation
bold_summary_bg_n Float Conditional background count of voxels
bold_summary_bg_p05 Float Conditional background 5th percentile
bold_summary_bg_p95 Float Conditional background 95th percentile
bold_summary_bg_stdv Float Conditional background standard deviation
bold_summary_fg_k Float Conditional foreground kurtosis
bold_summary_fg_mad Float Conditional foreground median absolute deviation
bold_summary_fg_mean Float Conditional foreground mean
bold_summary_fg_median Float Conditional foreground median absolute deviation
bold_summary_fg_n Float Conditional foreground count of voxels
bold_summary_fg_p05 Float Conditional foreground 5th percentile
bold_summary_fg_p95 Float Conditional foreground 95th percentile
bold_summary_fg_stdv Float Conditional foreground standard deviation
bold_tsnr Float Conditional Temporal SNR (tSNR, tsnr) is a simplified interpretation of the tSNR definition [Kruger2001]. We report the median value of the tSNR map calculated like: where _S_t is the average BOLD signal (across time), and _t is the corresponding temporal standard-deviation map.
accelnumreferencelines Float Recommended Acceleration number of reference lines
accelerationfactorpe Float Recommended Acceleration factor in the phase encode direction
acquisitionmatrix String 50 Recommended Dimensions of the acquired frequency /phase data before reconstruction. Multi-valued: frequency rowsfrequency columnsphase rowsphase columns. ID=DICOM:0018_1310
cogatlasid String 50 Recommended URL for task in the cognitive atlas (http://www.cognitiveatlas.org)
cogpoid String 50 Recommended URL for task in cogpowiki(http://wiki.cogpo.org)
coilcombinationmethod Float Recommended Almost all fMRI studies using phased-array coils use root-sum-of-squares (rSOS) combination, but other methods exist. The image reconstruction is changed by the coil combination method (as for the matrix coil mode above), so anything non-standard should be reported
conversionsoftware String 50 Recommended Software used to convert dicom to nifti
conversionsoftwareversion String 50 Recommended Release version of the software used to convert dicom to nifti
cardiactriggerdelaytimes Float Recommended Cardiac Trigger Delay Times
deviceserialnumber String 200 Recommended device serial number/ID
echotime Float Recommended Time in ms between the middle of the excitation pulse and the peak of the echo produced (kx=0). In the case of segmented k-space, the TE(eff) is the time between the middle of the excitation pulse to the peak of the echo that is used to cover the center of k-space (i.e.,-kx=0, ky=0). ID=DICOM:0018_0081
echotrainlength Float Recommended Number of lines in k-space acquired per excitation of the same volume regardless of the type of echo or the number of frames derived from them. ID:DICOM:0018_0091
effectiveechospacing Float Recommended The "effective" sampling interval, specified in seconds, between lines in the phase-encoding direction, defined based on the size of the reconstructed image in the phase direction. It is frequently, but incorrectly, referred to as "dwell time" (see DwellTime parameter below for actual dwell time). It is required for unwarping distortions using field maps. Note that beyond just in-plane acceleration, a variety of other manipulations to the phase encoding need to be accounted for properly, including partial fourier, phase oversampling, phase resolution, phase field-of-view and interpolation.2 This parameter is REQUIRED if corresponding fieldmap data is present.
flipangle Float Recommended Flip angle for the acquisition, specified in degrees. Corresponds to: DICOM Tag 0018, 1314 Flip Angle.
hardcopydevicesoftwareversion String 50 Recommended Manufacturers designation of the software of the device that created this Hardcopy Image (the printer). Corresponds to DICOM Tag 0018, 101A Hardcopy Device Software Version
imagetype String 50 Recommended Image Type
imagingfrequency Float Recommended Imaging Frequency
inplanephaseencodingdirection String 50 Recommended The axes of the in-plane phase encoding with respect to the frame. ID:DICOM:0018_1312
institutionaddress String 50 Recommended Mailing Address of the institution where the equipment is located.ID:DICOM:0008_0081
institutionname String 50 Recommended The name of the institution in charge of the equipment that produced the composite instances. Corresponds to DICOM Tag 0008, 0080 InstitutionName.
inst String 50 Recommended Text of the instructions given to participants before the scan. This is especially important in context of resting state fMRI and distinguishing between eyes open and eyes closed paradigms. instructions
inversiontime Float Recommended The inversion time (TI) for the acquisition, specified in seconds. Inversion time is the time after the middle of inverting RF pulse to middle of excitation pulse to detect the amount of longitudinal magnetization. Corresponds to DICOM Tag 0018, 0082 Inversion Time (please note that the DICOM term is in milliseconds not seconds).
mracquisitiontype String 50 Recommended Identification of data encoding scheme. ID:DICOM:0018_0023
magneticfieldstrength Float Recommended Nominal field strength of MR magnet in Tesla. ID:DICOM:0018_0087
manufacturer String 100 Recommended Manufacturer
manufacturersmodelname String 50 Recommended Manufacturer's model name of the equipment that produced the composite instances. Corresponds to DICOM Tag 0008, 1090 Manufacturers Model Name
matrixcoilmode Float Recommended A method for reducing the number of independent channels by combining in analog the signals from multiple coil elements. There are typically different default modes when using un-accelerated or accelerated (e.g. GRAPPA, SENSE) imaging
multibandaccelerationfactor Float Recommended The multiband factor, for multiband acquisitions.
numberofaverages Float Recommended Number of times a given pulse sequence is repeated before any parameter is changed. ID:DICOM:0018_0083
numberofphaseencodingsteps Float Recommended Total number of lines in k-space in the "y" direction collected during acquisition. ID:DICOM:0018_0089
num_vols_disc_scanner Float Recommended Number of volumes (“dummy scans”) discarded by the scanner (as opposed to those discarded by the user post hoc) before saving the imaging file. For example, a sequence that automatically discards the first 4 volumes before saving would have this field as 4. A sequence that doesn’t discard dummy scans would have this set to 0.
num_vols_disc_user Float Recommended Number of volumes ("dummy scans") discarded by the user before including the file in the dataset. If possible, including all of the volumes is strongly recommended. Please note that the onsets recorded in the _event.tsv file should always refer to the beginning of the acquisition of the first volume in the corresponding imaging file - independent of the value of NumberOfVolumesDiscardedByUser field.
numbershots Float Recommended The number of RF excitations need to reconstruct a slice or volume. Please mind that this is not the same as Echo Train Length which denotes the number of lines of k-space collected after an excitation.
parallelacquisitiontechnique String 50 Recommended The type of parallel imaging used (e.g. GRAPPA, SENSE). Corresponds to DICOM Tag 0018, 9078 Parallel Acquisition Technique.
par_red_fact_inplane Float Recommended The parallel imaging (e.g, GRAPPA) factor. Use the denominator of the fraction of k-space encoded for each slice. For example, 2 means half of k-space is encoded. Corresponds to DICOM Tag 0018, 9069 Parallel Reduction Factor In-plane.
partialfourier String 50 Recommended The fraction of partial Fourier information collected. Corresponds to DICOM Tag 0018, 9081 Partial Fourier.
patientposition String 50 Recommended Description of imaging subject's position relative to the equipment. ID:DICOM:0018_5100
percentphasefieldofview Float Recommended Ratio of field of view dimension in phase direction to field of view dimension in frequency direction, expressed as a percent. ID:DICOM:0018_0094
percentsampling Float Recommended Fraction of acquisition matrix lines acquired, expressed as a percent. ID:DICOM:0018_0093
phaseencodingdirection String 50 Recommended Possible values: i, j, k, i-, j-, k-. The letters i, j, k correspond to the first, second and third axis of the data in the NIFTI file. The polarity of the phase encoding is assumed to go from zero index to maximum index unless - sign is present (then the order is reversed - starting from the highest index instead of zero). PhaseEncodingDirection is defined as the direction along which phase is was modulated which may result in visible distortions. Note that this is not the same as the DICOM term InPlanePhaseEncodingDirection which can have ROW or COL values. This parameter is REQUIRED if corresponding fieldmap data is present or when using multiple runs with different phase encoding directions (which can be later used for field inhomogeneity correction).
pixelbandwidth Float Recommended Reciprocal of the total sampling period, in hertz per pixel. ID:DICOM:0018_0095
protocolname String 50 Recommended Description of the conditions under which the Series was performed. ID:DICOM:0018_1030
pulsesequencedetails String 50 Recommended Information beyond pulse sequence type that identifies the specific pulse sequence used (i.e. "Standard Siemens Sequence distributed with the VB17 software," "Siemens WIP ### version #.##," or "Sequence written by X using a version compiled on MM/DD/YYYY").
pulsesequencetype String 50 Recommended A general description of the pulse sequence used for the scan (i.e. MPRAGE, Gradient Echo EPI, Spin Echo EPI, Multiband gradient echo EPI).
receivecoilname String 50 Recommended Information describing the receiver coil. Corresponds to DICOM Tag 0018, 1250 Receive Coil Name, although not all vendors populate that DICOM Tag, in which case this field can be derived from an appropriate private DICOM field
repetitiontime Float Recommended The time in seconds between the beginning of an acquisition of one volume and the beginning of acquisition of the volume following it (TR). Please note that this definition includes time between scans (when no data has been acquired) in case of sparse acquisition schemes. This value needs to be consistent with the pixdim[4] field (after accounting for units stored in xyzt_units field) in the NIfTI header. This field is mutually exclusive with VolumeTiming and is derived from DICOM Tag 0018, 0080 and converted to seconds.
scanoptions String 50 Recommended Parameters of ScanningSequence. Corresponds to DICOM Tag 0018, 0022 Scan Options.
scanningsequence String 50 Recommended Description of the type of data acquired. Corresponds to DICOM Tag 0018, 0020 Scanning Sequence.
sequencename String 50 Recommended Manufacturers designation of the sequence name. Corresponds to DICOM Tag 0018, 0024 Sequence Name.
sequencevariant String 50 Recommended Variant of the ScanningSequence. Corresponds to DICOM Tag 0018, 0021 Sequence Variant.
sliceencodingdirection String 50 Recommended Possible values: i, j, k, i-, j-, k- (the axis of the NIfTI data along which slices were acquired, and the direction in which SliceTiming is defined with respect to). i, j, k identifiers correspond to the first, second and third axis of the data in the NIfTI file. A - sign indicates that the contents of SliceTiming are defined in reverse order - that is, the first entry corresponds to the slice with the largest index, and the final entry corresponds to slice index zero. When present, the axis defined by SliceEncodingDirection needs to be consistent with the ‘slice_dim’ field in the NIfTI header. When absent, the entries in SliceTiming must be in the order of increasing slice index as defined by the NIfTI header.
softwareversions String 50 Recommended Manufacturers designation of software version of the equipment that produced the composite instances. Corresponds to DICOM Tag 0018, 1020 Software Versions
taskdescription String 50 Recommended Longer description of the task.
taskname String 50 Recommended Name of the task. No two tasks should have the same name. Task label (task-) included in the file name is derived from this field by removing all non alphanumeric ([a-zA-Z0-9]) characters. For example task name faces n-back will corresponds to task label facesnback. A RECOMMENDED convention is to name resting state task using labels beginning with rest.
totalreadouttime Float Recommended This is actually the "effective" total readout time , defined as the readout duration, specified in seconds, that would have generated data with the given level of distortion. It is NOT the actual, physical duration of the readout train. If EffectiveEchoSpacing has been properly computed, it is just EffectiveEchoSpacing * (ReconMatrixPE - 1).3 . This parameter is REQUIRED if corresponding "field/distortion" maps acquired with opposing phase encoding directions are present (see 8.9.4).
totalscantimesec Float Recommended Total time of the scan in seconds
transmitcoilname String 50 Recommended Name of transmit coil used. ID:DICOM:0018_1251
variableflipangleflag String 50 Recommended Flip angle variation applied during image acquisition. ID:DICOM:0018_1315
acq_id String 50 Recommended Acquisition ID
run_id String 50 Recommended Run ID
session_id String 20 Recommended session ID/screening ID
contrast_bolus_ingredient String 50 Recommended Active ingredient of agent. Values MUST be one of: IODINE, GADOLINIUM, CARBON DIOXIDE, BARIUM, XENON Corresponds to DICOM Tag 0018,1048.
grad_set_type String 50 Recommended It should be possible to infer the gradient coil from the scanner model. If not, e.g. because of a custom upgrade or use of a gradient insert set, then the specifications of the actual gradient coil should be reported independently
mr_transmit_coil_seq String 50 Recommended This is a relevant field if a non-standard transmit coil is used. Corresponds to DICOM Tag 0018, 9049 MR Transmit Coil Sequence
partial_fourier_dir String 50 Recommended The direction where only partial Fourier information was collected. Corresponds to DICOM Tag 0018, 9036 Partial Fourier Direction.
image_modality String 20 Recommended Image modality MRI; PET; CT; SPECT; ultrasound; FA; X-Ray; spectroscopy; microscopy Computed Radiography; Computed Tomography; External Camera Photography; FA; General Microscopy; MRI; Magnetic Resonance; Magnetic Resonance Spectroscopy; Nuclear Medicine; Single Photon Emission Computed Tomography; Ultrasound
quest_instruct String 4,000 Recommended Questionnaire Instructions Questionnaire Instructions
Data Structure

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