Gareth,
Sorry for the problem you experienced. I am a main developer for GPU demons in ITK4.2. Would you please send me the images and the testing parameters you used?
Thank you for reporting this issue!
Bao
----- Original Message -----
From: James Gee
To: Baohua Wu ; Avants Brian
Sent: Thursday, July 19, 2012 9:30 AM
Subject: Fwd: [Insight-users] GPU Demons registration in ITK 4.2
Sent from my iPhone
Begin forwarded message:
From: Gareth Price <Gareth.Price at physics.cr.man.ac.uk>
Date: July 19, 2012 8:24:40 AM EDT
To: <insight-users at itk.org>
Subject: [Insight-users] GPU Demons registration in ITK 4.2
Hi there,
I was wondering if someone might be able to offer advice regarding the new ITK 4.2 GPU implementation of the demons algorithm.
I have an application using the standard CPU implementation to register 3D CT images (512x512x~70 voxels). This behaves perfectly when registering synthetic deformations to their original image. I typically use a smoothing kernel standard deviation of 10.0 with no update field smoothing. With my images, the metric reduces exponentially as expected from ~8000 to 350 over 50 iterations with the RMS update field change showing a similar but slower trend from ~0.08 to 0.04. After 50 iterations the solutions have made good progress towards the original images.
Porting this code to the GPU implementation following the examples in the itkGPUDemonsRegistrationFilterTests (i.e. swapping the internal image type for GPUImageType and GPUDemonsRegistrationFilter for DemonsRegistrationFilter) provides an immediate ~x15 increase in speed on my machine (GeForce GTX480). However using the same input data and smoothing parameters, the metric and RMS update field trends, although still exponential show changes from ~8000 to 1500 (metric) and ~0.3 to 0.2 (update field). The result is that the deformation field produced is much too large. Changing smoothing parameters does not change this behaviour, whilst enabling update field smoothing crashes the process (in GPUDemonsRegistrationFilter::ApplyUpdate). It is very strange that the similarity metric is continuing to reduce as the deformation field pushes the moving image through and past its correct fixed image alignment.
Would someone be able to tell me if this is expected behaviour/are known bugs, or offer advice if I am using the GPU registration filter incorrectly?
Many thanks, Gareth
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