04-03-2020
Bug in New User Registration Process (No Registration Complete Message)
There is bug in the new member registration process.
This bug appeared after we paused registration and moved to the new forums in our initial test mode.
When a new user registers now (here), the registration processes completes (normally) but the "Registration Success" message does not appear in the registration feedback message.
However, the user can login.
I have already retired this code base and do not plan to fix this bug since we will be moving to a new forum soon.
Thank you for your patience.
One option is to disable new user registrations again here, but for now I will leave it "as-is" since we will get the new forums running again soon (we hope!).
This User Gave Thanks to Neo For This Post:
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ANTS(1) User Commands ANTS(1)
NAME
ANTS - part of ANTS registration suite
DESCRIPTION
Example usage:
./ANTS ImageDimension -m MI[fixedimage.nii.gz,movingimage.nii.gz,1,32] -o Outputfname.nii.gz -i 30x20x0 -r Gauss[3,1] -t Elast[3]
Compulsory arguments:
ImageDimension: 2 or 3 (for 2 or 3 Dimensional registration)
-m: Type of similarity model used for registration.
For intramodal image registration, use:
CC = cross-correlation MI = mutual information PR = probability mapping MSQ = mean square difference
For intermodal image registration, use:
MI = mutual information PR = probability mapping
-o Outputfname.nii.gz: the name of the resulting image.
-i Max-iterations in format: JxKxL, where:
J = max iterations at coarsest resolution (here, reduce by power of 2^2) K = middle resolution iterations (here,reduce by power of
2) L = fine resolution iterations (here, full resolution). This level takes much more time per iteration!
Adding an extra value before JxKxL (i.e. resulting in IxJxKxL) would add another iteration level.
-r Regularization
-t Type of transformation model used for registration
For elastic image registration, use:
Elast = elastic transformation model (less deformation possible)
For diffeomorphic image registration, use:
Syn[GradStep,TimePoints,IntegrationStep] --geodesic 2 = SyN with time with arbitrary number of time points in time discretization
SyN[GradStep,2,IntegrationStep] = SyN with time optimized specifically for 2 time points in the time discretization SyN[GradStep] =
Greedy SyN, typicall GradStep=0.25 Exp[GradStep,TimePoints] = Exponential GreedyExp = Diffeomorphic Demons style exponential mapping
Please use the `ANTS -h ` call or refer to the ANTS.pdf manual or antsIntroduction.sh script for additional information and typical
values for transformation models
ANTS 1.9 May 2012 ANTS(1)