[ITK] [ITK-users] Connected Threshold Filter crashes but only for large images

[Michael Pinkert]

Hi,

I think the problem may be unique to the data set I was working with.  New
scans I acquired from different patients have been working fine, so it looks
like it is something wrong with the images that is the issue.  Thank you for
your help, and I'll keep your advice in mind in case I run into this problem
again.

Best regards,
Michael Pinkert


Bradley Lowekamp wrote
> Hello,
> 
> I have had great success running this algorithm on very large data sets.
> And consider the implementation very robust.
> 
> There could be something different about your pipeline, or something
> unique about your image, or how you compiled it.
> 
> First are you running 32 or 64-bits? Perhaps you are running out of
> memory?
> 
> Perhaps there is something odd about your pipeline. If you just do a
> ImageFileRead->Connected Threshold->ImageFileWrite does it still crash?
> 
> If you are familiar with Python, perhaps you could try running this filter
> with a binary download of SimpleITK? This would check to see if there is
> something intrinsically wrong with the algorithm?
> 
> Just some ideas to help narrow it down...
> Brad
> 
> 
> On Jul 15, 2014, at 12:27 PM, Michael Pinkert <

> mpinkert@

> > wrote:
> 
>> Hi everyone,
>> 
>> I am working with sets of 3D MRI data from multiple years for my
>> research. 
>> I am using the connected threshold filter in a pipeline after a binary
>> thresholding procedure using Otsu segmentation.
>> 
>> The algorithm functions when there are 124 slices in the image, but
>> crashes
>> with an abort message when there are 248 slices and when there are 156
>> slices.  
>> 
>> I have tested this with multiple data sets and the pattern holds.  The
>> strange part is that this still happens even if I resample the number of
>> slices down to 124, so I really am confused as to what is happening.
>> 
>> Is there any reason why the filter would be crashing for images that are
>> too
>> large like this, even after being resampled smaller?
>> 
>> Best regards,
>> Michael Pinkert
>> 
>> 
>> 
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