# The value of FA.nii.gz **URL:** \ **Category:** Uncategorized\ **Created:** [September 8, 2016, 9:13am UTC](https://community.mrtrix.org/t/the-value-of-fa-nii-gz/429 "2016-09-08T09:13:04Z")\ **Posts on this page:** 1\ **Showing post:** 3
**Author:** ![jdtournier](https://community.mrtrix.org/user_avatar/community.mrtrix.org/jdtournier/32/2594_2.png) [@jdtournier](https://community.mrtrix.org/u/jdtournier)\ **Post date:** [September 8, 2016, 4:03pm UTC](https://community.mrtrix.org/t/the-value-of-fa-nii-gz/429/3 "2016-09-08T16:03:47Z")
Agreed, those regions with FA \> 1 are overwhelming around the edge of the brain, and most likely due to background noise. You may chose to remove them using a more aggressive mask, but it’s by no means a requirements - it simply makes the images nicer to display. Just to explain how you can get FA \> 1: one way of defining FA is as the ratio of the variance in the eigenvalues of the tensor to their root-mean-square value, scaled such that the maximum _physically possible_ FA value is 1. But what happens in noisy regions is that the _b_=0 and DW intensities are similar, so that the ratio of DWI to _b_=0 can be greater than 1, which leads to a _negative_ ADC value. This is clearly non-physical, but nonetheless allowed by the fitting procedure. When this happens, it will lead to a greater variance than expected, and consequently an FA value greater than 1. While some fitting routines do constrain the eigenvalues to be positive, this requires expensive non-linear fitting routines, and we don’t see a huge benefit to using them since the problem is largely confined to non-brain regions anyway… --- _[View the full topic](https://community.mrtrix.org/t/the-value-of-fa-nii-gz/429)._