[Insight-users] vessel enhancing diffusion filter (release 200)

[Oleksandr Dzyubak]

Hi Luis,

First of all many thanks all of you for such a good filter, "Vessel 
enhancing diffusion filter".
With great pleasure I read the article from the the IJ distribution and 
the references therein.

Since I am working on vessels, of course, I was tempted to give that 
filter a try. So I did.
As well as Laura, I got the same error message and following your advice
and formula, I calculated the memory request.

I tested the filter using an image 565x440x100 pixels.
BTW, why 6 in your formula "sizeof(double) x 6 bytes per pixel"?
Do you store some intermediate results all the time?
Lets calculate memory. In my case sizeof(double)=8.

octave:2> 8*6*(565*440*100)
ans = 1193280000

OK. Filter + ImageItself = 1.19 +  0.0497 ~ 1.2397 GB

I have 2 GB + 2 GB (swap). As you say, I almost hit the limit but some 
piece is still left.
Does a swap part count? I cropped the original image (which is 100 times 
larger then the one I used)
down to 47MB just to test the filter and even with such a small image 
size the filter fails to allocate memory?

Does it mean that this filter has no use for boxes with limited resources?

BTW, the only "itkAnisotropicDiffusionVesselEnhancementImageFilterTest" 
fails.
The other one, 
"itkMultiScaleHessianSmoothed3DToVesselnessMeasureImageFilterTest" works 
fine.

Just by luck or you implemented another memory model?

Thanks,

Alex

Luis Ibanez wrote:
>
> Hi Laura,
>
> This is annoying, but normal.
>
> This code computes Hessians of images, which in 3D requires
> the allocation of sizeof(double) x 6 bytes per pixel.
>
> That is, you will need 48 bytes per pixel of your image
> in order to store the resulting Hessian alone. There will be
> of course additional intermediate allocations.
>
> If you need to process large images you may need a 64bits
> machine with a larger memory...
>
> What is the actual size (in pixels) of the image that
> you are processing ?
>
> Can you process selected regions of the image ?
>
> Usually there is a lot of empty (or at least, non interesting)
> space in medical images. You could use the RegionOfInterest
> filter to reduce the vessel enhancing processing to smaller
> section of the image.
>
>
> Please let us know,
>
>
>     Thanks
>
>
>        Luis
>
>
>
>
>
> ---------------------------------
> Laura Fernandez de Manuel wrote:
>> Hi all,
>>  
>> We have been checking the implementation of the "Vessel Enhancing 
>> Diffusion Filter" depicted here:
>>  
>> http://insight-journal.org/midas/handle.php?handle=1926/558
>>  
>> although it works properly with the example 3D images provided 
>> (ranging from around 30 to 250 KB) we didn't succeed to make it work 
>> in images any larger (5MB images failed already for instance). We 
>> work in a system with 4GB RAM so we don't know which can be the 
>> source of the "Failed to allocate memory for image" errors that we 
>> get. Here, I attach the error message we get:
>>  
>> ------------------------------------------------------------------------------------------------------ 
>>
>> ./itkAnisotropicDiffusionVesselEnhancementImageFilterTest.exe 
>> image00_2.mhd image_2Enhanced.mhd
>> Reading input image : image00_2.mhd
>> Enhancing vessels.........: image00_2.mhd
>> Iteration:      0
>> Computing vesselness for scale with sigma= 0.2
>> Exception caught:
>> itk::ExceptionObject (0138FB20)
>> Location: "class itk::SymmetricSecondRankTensor<double,3> *__thiscall 
>> itk::ImportImageContainer<unsigned long,class 
>> itk::SymmetricSecondRankTensor<double,3> >:: AllocateElements 
>> (unsigned long) const"
>> File: itk3.6.0\code\common\itkImportImageContainer.txx
>> Line: 193
>> Description: Failed to allocate memory for image.
>> ------------------------------------------------------------------------------------------------------ 
>>
>>  
>> Thanks a lot!
>>  
>> carlos & laura
>>
>>  
>>  
>>
>>
>> ------------------------------------------------------------------------
>>
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