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Copy file name to clipboardExpand all lines: nibabies/data/reports-spec.yml
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desc: conform
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extension: [.html]
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- bids: {datatype: figures, suffix: dseg}
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caption: This panel shows the template anatomical image (if several were found),
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with contours delineating the detected brain mask and brain tissue
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segmentations.
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caption: This panel shows the template anatomical image (if several were found), with contours delineating the detected brain mask and brain tissue segmentations.
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subtitle: Brain mask and brain tissue segmentation of anatomical reference
caption: Spatial normalization of the anatomical reference image to the <code>{space}</code>
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template.
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description: Results of nonlinear alignment of the anatomical reference one or more template
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space(s). Hover on the panels with the mouse pointer to transition between both
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spaces.
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caption: Spatial normalization of the anatomical reference image to the <code>{space}</code> template.
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description: Results of nonlinear alignment of the anatomical reference one or more template space(s). Hover on the panels with the mouse pointer to transition between both spaces.
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static: false
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subtitle: Spatial normalization of the anatomical reference
caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions
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along the phase-encoding direction of the image. Some scanners produce a <em>B<sub>0</sub></em>
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mapping of the field, using Spiral Echo Imaging (SEI) or postprocessing a "phase-difference"
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acquisition. The plot below shows an anatomical "magnitude" reference and the corresponding
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fieldmap.
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description: Hover over the panels with the mouse pointer to also visualize the intensity of the
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field inhomogeneity in Hertz.
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caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions along the phase-encoding direction of the image. Some scanners produce a <em>B<sub>0</sub></em> mapping of the field, using Spiral Echo Imaging (SEI) or postprocessing a "phase-difference" acquisition. The plot below shows an anatomical "magnitude" reference and the corresponding fieldmap.
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description: Hover over the panels with the mouse pointer to also visualize the intensity of the field inhomogeneity in Hertz.
caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions
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along the phase-encoding direction of the image. A Gradient-Recalled Echo (GRE) scheme for the
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mapping of the <em>B<sub>0</sub></em> inhomogeneities by subtracting the phase maps obtained at
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two subsequent echoes. The plot below shows an anatomical "magnitude" reference and the corresponding
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fieldmap.
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description: Hover over the panels with the mouse pointer to also visualize the intensity of the
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field inhomogeneity in Hertz.
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caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions along the phase-encoding direction of the image. A Gradient-Recalled Echo (GRE) scheme for the mapping of the <em>B<sub>0</sub></em> inhomogeneities by subtracting the phase maps obtained at two subsequent echoes. The plot below shows an anatomical "magnitude" reference and the corresponding fieldmap.
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description: Hover over the panels with the mouse pointer to also visualize the intensity of the field inhomogeneity in Hertz.
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static: false
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subtitle: "Preprocessed mapping of phase-difference acquisition"
caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions
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along the phase-encoding direction of the image. Utilizing two or more images with different
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phase-encoding polarities (PEPolar) or directions, it is possible to estimate the inhomogeneity
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of the field. The plot below shows a reference EPI (echo-planar imaging) volume generated
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using two or more EPI images with varying phase-encoding blips.
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description: Hover on the panels with the mouse pointer to also visualize the intensity of the
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inhomogeneity of the field in Hertz.
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caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions along the phase-encoding direction of the image. Utilizing two or more images with different phase-encoding polarities (PEPolar) or directions, it is possible to estimate the inhomogeneity of the field. The plot below shows a reference EPI (echo-planar imaging) volume generated using two or more EPI images with varying phase-encoding blips.
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description: Hover on the panels with the mouse pointer to also visualize the intensity of the inhomogeneity of the field in Hertz.
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static: false
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subtitle: "Preprocessed estimation with varying Phase-Endocing (PE) blips"
caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions
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along the phase-encoding direction of the image. Utilizing an <em>anatomically-correct</em> acquisition
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(for instance, T1w or T2w), it is possible to estimate the inhomogeneity of the field by means of nonlinear
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registration. The plot below shows a reference EPI (echo-planar imaging) volume generated
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using two or more EPI images with the same PE encoding, after alignment to the anatomical scan.
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description: Hover on the panels with the mouse pointer to also visualize the intensity of the
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inhomogeneity of the field in Hertz.
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caption: Inhomogeneities of the <em>B<sub>0</sub></em> field introduce (oftentimes severe) spatial distortions along the phase-encoding direction of the image. Utilizing an <em>anatomically-correct</em> acquisition (for instance, T1w or T2w), it is possible to estimate the inhomogeneity of the field by means of nonlinear registration. The plot below shows a reference EPI (echo-planar imaging) volume generated using two or more EPI images with the same PE encoding, after alignment to the anatomical scan.
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description: Hover on the panels with the mouse pointer to also visualize the intensity of the inhomogeneity of the field in Hertz.
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static: false
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subtitle: "Preprocessed estimation by nonlinear registration to an anatomical scan (“<em>fieldmap-less</em>”)"
caption: The estimated fieldmap was aligned to the corresponding EPI reference
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with a rigid-registration process of the magintude part of the fieldmap,
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using <code>antsRegistration</code>.
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Overlaid on top of the co-registration results, the displacements along the
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phase-encoding direction are represented in arbitrary units.
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Please note that the color scale is centered around zero (i.e. full transparency),
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but the extremes might be different (i.e., the maximum of red colors could be
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orders of magnitude above or below the minimum of blue colors.)
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caption: The estimated fieldmap was aligned to the corresponding EPI reference with a rigid-registration process of the magintude part of the fieldmap, using <code>antsRegistration</code>. Overlaid on top of the co-registration results, the displacements along the phase-encoding direction are represented in arbitrary units. Please note that the color scale is centered around zero (i.e. full transparency), but the extremes might be different (i.e., the maximum of red colors could be orders of magnitude above or below the minimum of blue colors.)
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subtitle: Estimated fieldmap and alignment to the corresponding EPI reference
caption: The dataset contained some fieldmap information, but the argument <code>--force-syn</code>
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was used. The higher-priority SDC method was used. Here, we show the results
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of performing SyN-based SDC on the EPI for comparison.
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caption: The dataset contained some fieldmap information, but the argument <code>--force-syn</code> was used. The higher-priority SDC method was used. Here, we show the results of performing SyN-based SDC on the EPI for comparison.
caption: FSL <code>flirt</code> was used to generate transformations from EPI
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space to T1 Space - BBR refinement rejected. Note that Nearest Neighbor interpolation
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is used in the reportlets in order to highlight potential spin-history and other
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artifacts, whereas final images are resampled using Lanczos interpolation.
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caption: FSL <code>flirt</code> was used to generate transformations from EPI space to T1 Space - BBR refinement rejected. Note that Nearest Neighbor interpolation is used in the reportlets in order to highlight potential spin-history and other artifacts, whereas final images are resampled using Lanczos interpolation.
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subtitle: Alignment of functional and anatomical MRI data (volume based)
caption: <code>mri_coreg</code> (FreeSurfer) was used to generate transformations
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from EPI space to T1 Space - <code>bbregister</code> refinement rejected. Note
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that Nearest Neighbor interpolation is used in the reportlets in order to highlight
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potential spin-history and other artifacts, whereas final images are resampled
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using Lanczos interpolation.
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caption: <code>mri_coreg</code> (FreeSurfer) was used to generate transformations from EPI space to T1 Space - <code>bbregister</code> refinement rejected. Note that Nearest Neighbor interpolation is used in the reportlets in order to highlight potential spin-history and other artifacts, whereas final images are resampled using Lanczos interpolation.
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subtitle: Alignment of functional and anatomical MRI data (volume based)
caption: FSL <code>flirt</code> was used to generate transformations from EPI-space
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to anatomical space - The white matter mask calculated with FSL <code>fast</code> (brain
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tissue segmentation) was used for BBR. Note that Nearest Neighbor interpolation
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is used in the reportlets in order to highlight potential spin-history and other
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artifacts, whereas final images are resampled using Lanczos interpolation.
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caption: FSL <code>flirt</code> was used to generate transformations from EPI-space to anatomical space - The white matter mask calculated with FSL <code>fast</code> (brain tissue segmentation) was used for BBR. Note that Nearest Neighbor interpolation is used in the reportlets in order to highlight potential spin-history and other artifacts, whereas final images are resampled using Lanczos interpolation.
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static: false
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subtitle: Alignment of functional and anatomical MRI data (surface driven)
caption: <code>bbregister</code> was used to generate transformations from EPI-space
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to anatomical space. Note that Nearest Neighbor interpolation is used in the reportlets
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in order to highlight potential spin-history and other artifacts, whereas final
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images are resampled using Lanczos interpolation.
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caption: <code>bbregister</code> was used to generate transformations from EPI-space to anatomical space. Note that Nearest Neighbor interpolation is used in the reportlets in order to highlight potential spin-history and other artifacts, whereas final images are resampled using Lanczos interpolation.
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static: false
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subtitle: Alignment of functional and anatomical MRI data (surface driven)
caption: Brain mask calculated on the BOLD signal (red contour), along with the
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regions of interest (ROIs) used in <em>a/tCompCor</em> for extracting
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physiological and movement confounding components.<br />
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The <em>anatomical CompCor</em> ROI (magenta contour) is a mask combining
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CSF and WM (white-matter), where voxels containing a minimal partial volume
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of GM have been removed.<br />
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The <em>temporal CompCor</em> ROI (blue contour) contains the top 2% most
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variable voxels within the brain mask.
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caption: Brain mask calculated on the BOLD signal (red contour), along with the regions of interest (ROIs) used in <em>a/tCompCor</em> for extracting physiological and movement confounding components.<br /> The <em>anatomical CompCor</em> ROI (magenta contour) is a mask combining CSF and WM (white-matter), where voxels containing a minimal partial volume of GM have been removed.<br /> The <em>temporal CompCor</em> ROI (blue contour) contains the top 2% most variable voxels within the brain mask.
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subtitle: Brain mask and (anatomical/temporal) CompCor ROIs
caption: The cumulative variance explained by the first k components of the
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<em>t/aCompCor</em> decomposition, plotted for all values of <em>k</em>.
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The number of components that must be included in the model in order to
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explain some fraction of variance in the decomposition mask can be used
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as a feature selection criterion for confound regression.
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caption: The cumulative variance explained by the first k components of the <em>t/aCompCor</em> decomposition, plotted for all values of <em>k</em>. The number of components that must be included in the model in order to explain some fraction of variance in the decomposition mask can be used as a feature selection criterion for confound regression.
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subtitle: Variance explained by t/aCompCor components
caption: Summary statistics are plotted, which may reveal trends or artifacts
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in the BOLD data. Global signals calculated within the whole-brain (GS), within
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the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD
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signal in their corresponding masks. DVARS and FD show the standardized DVARS
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and framewise-displacement measures for each time point.<br />
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A carpet plot shows the time series for all voxels within the brain mask,
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or if <code>--cifti-output</code> was enabled, all grayordinates.
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Voxels are grouped into cortical (dark/light blue), and subcortical (orange)
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gray matter, cerebellum (green) and white matter and CSF
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(red), indicated by the color map on the left-hand side.
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caption: Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br /> A carpet plot shows the time series for all voxels within the brain mask, or if <code>--cifti-output</code> was enabled, all grayordinates. Voxels are grouped into cortical (dark/light blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.
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