This panel shows a mosaic enhancing the background around the head. Artifacts usually unveil themselves in the air surrounding the head, where no signal sources are present.
This panel shows a mosaic of the brain. This mosaic is the most suitable to screen head-motion intensity inhomogeneities, global/local noise, signal leakage (for example, from the eyeballs and across the phase-encoding axis), etc.
The hat-mask calculated internally by MRIQC. Some metrics will use this mask, for instance, to find out artifacts and estimate the spread of gaussian noise added to the signal. This mask leaves out the air around the face to avoid measuring noise sourcing from the eyeballs and their movement.
The noise fit internally estimated by MRIQC to calculate the QI1 index proposed by Mortamet et al. (2009).
Mask of artifactual intensities identified within the hat-mask.
Brain mask as internally extracted by MRIQC. Defects on the brainmask could indicate problematic aspects of the image quality-wise.
A mask of the head calculated internally by MRIQC.
Brain tissue segmentation, as internally extracted by MRIQC. Defects on this segmentation, as well as noisy tissue labels could indicate problematic aspects of the image quality-wise.
This panel shows a quick-and-dirty nonlinear registration into the MNI152NLin2009cAsym
template accessed with TemplateFlow.
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