FBER scores of -1

I’m having subjects get a fiber score of -1. Not sure what the cause is. Found many with this error: estimated signal variation in background is too small. Not all of those with the error got a fber of -1. Thoughts? What could cause this (score of -1)? And is it related to the error?

Hello,

I am also interested in this topic. Has anyone determined the cause of a FBER score of -1 (MRIQC of T1w data)?

Best,
Jenna

Here’s the code from mriqc for calculating FBER. Looks like if the median of the square of airmask is less than .001 it will return -1:

    fg_mu = np.median(np.abs(img[headmask > 0]) ** 2)

    airmask = np.ones_like(headmask, dtype=np.uint8)
    airmask[headmask > 0] = 0
    if rotmask is not None:
        airmask[rotmask > 0] = 0
    bg_mu = np.median(np.abs(img[airmask == 1]) ** 2)
    if bg_mu < 1.0e-3:
        return -1.0
    return round(float(fg_mu / bg_mu), decimals)

Link to github