[ITK-users] 2D rigid transformation

[Yaniv, Ziv Rafael (NIH/NLM/LHC) [C]]

Hello Pietro,

You should use the ExhaustiveOptimizerv4 (http://www.itk.org/Doxygen/html/classitk_1_1ExhaustiveOptimizerv4.html) which allows you to set a grid on which the similarity metric is evaluated.

If you are familiar with python, then the following SimpleITK notebook may be of use to you (see last section): https://github.com/zivy/SimpleITK-Notebook-Staging/blob/master/registration3.ipynb

     regards
              Ziv

From: Pietro Nardelli <p.nardelli at umail.ucc.ie<mailto:p.nardelli at umail.ucc.ie>>
Date: Friday, May 15, 2015 at 2:13 PM
To: "insight-users at itk.org<mailto:insight-users at itk.org>" <insight-users at itk.org<mailto:insight-users at itk.org>>
Subject: [ITK-users] 2D rigid transformation

Hello guys,

is there a way to have a 2D rigid registration that uses a specific number of rotations and chooses the best one? I have two images that are simply rotated with respect to each other, and I would like to register them using for example 36 rotations (therefore computing the mean squared error every 10 degrees). At the moment I am using the 2DRigidTransform with a specified center, with a regular step descent optimizer and the ImageRegistrationMethodv4. I saw that the transform has the function SetFixedParameters() but I am not really sure whether I understand correctly that that would tell the optimizer the angles (and translations) to use at every iteration. Could anyone please clarify this?

Thank you very much,
Pietro