Measures based on noise measurements |
CJV |
The coefficient of joint variation of GM and WM was proposed as objective function by Ganzetti et al. [30] for the optimization of INU correction algorithms. Higher values are related to the presence of heavy head motion and large INU artifacts. |
CNR |
The contrast-to-noise ratio [31] is an extension of the SNR calculation to evaluate how separated the tissue distributions of GM and WM are. Higher values indicate better quality. |
SNR |
MRIQC includes the the signal-to-nose ratio calculation proposed by Dietrich et al. [32], using the air background as noise reference. Additionally, for images that have undergone some noise reduction processing, or the more complex noise realizations of current parallel acquisitions, a simplified calculation using the within tissue variance is also provided. |
QI2
|
The second quality index of [12] is a calculation of the goodness-of-fit of a χ2 distribution on the air mask, once the artifactual intensities detected for computing the QI1 index have been removed. The description of the QI1 is found below. |
Measures based on information theory |
EFC |
The entropy-focus criterion [33] uses the Shannon entropy of voxel intensities as an indication of ghosting and blurring induced by head motion. Lower values are better. |
FBER |
The foreground-background energy ratio [14] is calculated as the mean energy of image values within the head relative the mean energy of image values in the air mask. Consequently, higher values are better. |
Measures targeting specific artifacts |
INU |
MRIQC measures the location and spread of the bias field extracted estimated by the inu correction. The smaller spreads located around 1.0 are better. |
QI1
|
The first quality index of [12] measures the amount of artifactual intensities in the air surrounding the head above the nasio-cerebellar axis. The smaller QI1, the better. |
WM2MAX |
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]. |
Other measures |
FWHM |
The full-width half-maximum [34] is an estimation of the blurriness of the image using AFNI’s 3dFWHMx. Smaller is better. |
ICVs |
Estimation of the icv of each tissue calculated on the FSL FAST’s segmentation. Normative values fall around 20%, 45% and 35% for cerebrospinal fluid (CSF), WM and GM, respectively. |
rPVE |
The residual partial volume effect feature is a tissue-wise sum of partial volumes that fall in the range [5%-95%] of the total volume of a pixel, computed on the partial volume maps generated by FSL FAST. Smaller residual partial volume effects (rPVEs) are better. |
SSTATs |
Several summary statistics (mean, standard deviation, percentiles 5% and 95%, and kurtosis) are computed within the following regions of interest: background, CSF, WM, and GM. |
TPMs |
Overlap of tissue probability maps estimated from the image and the corresponding maps from the ICBM nonlinear-asymmetric 2009c template [35]. |