[MINC-users] N3

[joel-bruss@uiowa.edu]

Currently I have data from a GE 1.5T, and Siemens 1.5 and 3T (Avanto and Trio)
scanners.  I am looking for a way to bias-correct these images so that they can
be used with Gray/White segmentation and other volumetrics.  My data is in
16-bit Analyze format and I have a minc converter (ana2mnc).  When I run
nu_correct, with default parameters (-V1.0) as well as specifying a mask of the
brain image, I get very awful results.  In my 124-slice volume, there are
regions where the image is totally washed out (5-10 slice runs) and others where
the brain looks nice but the bias-correction happened outside of the skull. 
When specifying for temp files to be saved as well as a tempdir, after
converting the bias field, it looks like a perfectly uniform smoothing kernel
(ovular/egg shape) which is definitely not what the bias appears as (more polar,
specifically in the frontal lobe).  I've tried downloading the test data but am
unsure of how to even work with it.  I've read Sled et al's IEEE paper but don't
find it that useful in configuring nu_correct.  Also, I set the max iteration
for 150 but it runs through 3 iterations (in about 2 minutes) and says that it
is done.  Is this really possible?

Is there a help file, other than the README, or tutorial out there?  Any
suggestions on how to configure nu_correct?  Should I use a different Minc
converter?  Is it OK to use 16-bit images or do they need to be 8-bit?  Any help
would be useful right now.

Thanks for your time

-Joel