Hi everyone,<br><br>I'm trying to make the Diffeomorphic Demons class work nicely. (I tried the few other demons variants - this one works best for my data.)<br><br>(1) I've tried it on a bunch of cardiac short axis images - to register the end systole slices to the topmost slice at end diastole - then I apply the deformation field Diffeo Demons gives me to a manual segmentation of the end diastole first slice, to get an automatic segmentation of the end systole slices. I'm doing all this slice by slice (in 2D). <br>
I have noticed that the registration process does not seem to do well
when the intra-ventricular cardiac muscles are prominent and deform a
lot between slices. This is not good if I am trying to estimate the
volume of the heart. :(<br>
In general, the technique does not do well in capturing details, even if well defined. (I guess I'm asking for too much from a registration algorithm.....) Are my observations correct or am I making a mistake somewhere? <br>
<br>(2) Before Diffeo Demons, I perform a centered rigid transform. However, for my data, it does not seem to be really needed as the optimum transformation parameters found are rather negligible. I use it anyway. <br><br>
(3) To better understand things, I tried it to repeat the experiment for the binary circular and C-shaped images given here: <a href="http://www.insight-journal.org/browse/publication/154">http://www.insight-journal.org/browse/publication/154</a><br>
Unfortunately I have not been able to get the results as advertised even if I set number of iterations to 10,000. I guess there are two reasons for this: (a) Something wrong with the images that I recreated (b) I have not really tried experimenting with the few other parameters available. Maybe something in those? (c) Some possible mistake in my code. Has anyone tried these images?<br>
<br>Thanks in advance,<br>Harish<br><br><br><br><br><br>