[Insight-users] Similarity Transform in 2D

[Maureen Haining]

Hello Users,
I have two images that are essentially aligned that I am using to experiment
with the Similarity Transform with Regular Step Gradient Descent Optimizer
(I am using example 7). The fixed image is a traced black and white boundary
image of moving image. I am having trouble understanding the results.

Result =

 Scale         = 4.15432

 Angle (radians) 0.00397598

 Angle (degrees) 0.227807

 Center X      = 374.818

 Center Y      = 361.912

 Translation X = -0.171362

 Translation Y = -0.684359

 Iterations    = 500

 Metric value  = 1337.12


I am surprised to see a scaling factor introduced. I have set the
optimizerScales to 1 (scale)  and 1 (angle). And indeed the moving image is
scaled down by about a factor of 4. Can anyone shed any light on this for
me?


Also, can anyone recommend a good reference book that is an introduction to
registration techniques and would explain from an application viewpoint the
pros and cons of particular transformations. I have Terry Yoo's book but I
would like something more introductory. I have also read the itk software
guide but would like to find another reference.


Thanks for any help you can give.

Maureen
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