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It is also true that plastimatch shouldn't crash. And the scores you showed in the screen capture look like nonsense, those values are way too high. So there appears to be a bug somewhere. Would you be able to share your images and command file?
Greg
________________________________________
From: 'Paolo Zaffino' via Plastimatch <plast...@googlegroups.com>
Sent: Wednesday, April 19, 2023 5:50 AM
To: plast...@googlegroups.com
Subject: Re: [Plastimatch] Registration failures and crashes
External Email - Use Caution
Hi,
in my opinion a lambda value equal to 0.1 it is too much.
Plastimatch quits because it doesn't find any suitable solution, due to the too strong penalization.
Let's try some smaller value (0.0001 maybe?).
It's a trade-off: you have to penalize but not too much.
Best,
Paolo
On 4/19/23 05:42, Jeremy Lim wrote:
Hi,
I have been doing lung registrations while varying the DIR regularisation term λ and was wondering if you could provide some insight to the behaviour of Plastimatch below:
Registration failure
There was one case where using λ = 0.1 resulted in a deformed image that was completely uniform (zero everywhere) and 100% negative Jacobian within the lungs. The output as the registration completed is shown below.
[Registration failure.png]
However, varying λ slightly to 0.1001 resulted in a successful registration with less than 1% negative Jacobian within the lungs.
Plastimatch crash
There was another case where Plastimatch would crash at stage 5 of the registration and it would still crash despite changing the value of λ. The registration was repeated several times and the crash always occured at the same iteration with the same SCORE, MSE, etc. This was expected as my experience with Plastimatch thus far was that it was deterministic and results can be reproduced exactly.
[X]
However, when I ran the registration repeatedly any changes, there were some occasions, about 15% of attempts, where the registration would continue, that may result in a failure or success (all 6 stages of DIR completed). When it failed, it had the following output and deformed image:
[Output.png]
[Output.png]
The registration was successful twice in around 40 attempts. However, the MSE after the registrations were slightly different (27765.7 vs. 27738.1) and very slight differences could be seen in the deformed images. Is there some randomness introduced somewhere in the registration process that could explain this behaviour?
Another thing I observed with this patient was that the crash could be avoided if the pixel dimensions and offset of the MHAs were rounded up (e.g. to the 3rd decimal place). What could be the reason for this?
Kind regards,
Jeremy
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