This algorithm normalizes conventional brain MRI scans [1] by detecting a latent subdistribution of normal tissue and linearly scaling the histogram of images.

REQUIREMENTS:

Bias-corrected (N3 or N4) T1-weighted or T2-weighted images, ideally either skull-stripped or rigidly aligned to MNI space.

USAGE:

Launch the WhiteStripe UI using the 'Applications -> WhiteStripe Normalization' menu option.
Specify the Input and Output files and different parameters (defaults are populated).
Click on 'Run WhiteStripe" and the results can be seen in a slice format using "Toggle Mask/Image" checkbox.
Use 'Level Display' when needed.

This application is also available as with a stand-alone CLI for data analysts to build pipelines around, using the following example command:
```
WhiteStripe.exe -i C:/inputImage.nii.gz -o C:/outputImage.nii.gz
```

NOTE: WhiteStripe uses the KernelFit library from Lentner (https://github.com/glentner/KernelFit).

Reference:

R.T.Shinohara, E.M.Sweeney, J.Goldsmith, N.Shiee, F.J.Mateen, P.A.Calabresi, S.Jarso, D.L.Pham, D.S.Reich, C.M.Crainiceanu, Australian Imaging Biomarkers Lifestyle Flagship Study of Ageing, Alzheimer's Disease Neuroimaging Initiative. "Statistical normalization techniques for magnetic resonance imaging", Neuroimage Clin. 6:9-19, 2014. DOI:10.1016/j.nicl.2014.08.008