[ITK-users] R-SimpleITK LabelStatisticsImageFilter 3D Error

Wed Jul 6 08:26:43 EDT 2016

Hello,

Did you compile R SimpleITK from a very recent version of the SimpleITK master branch from git?

There have been a lot of improvements for the R wrapping, and required improvement with SWIG too. This looks like an problem that has been fixed related R reference counting. 

SimpleITK is smart enough to know when to call the 3D or 2D version of a filter. It also knows the pixel types of the inputs and calls the correct template combinations for the ITK filter automatically. When the filter is not instantiated with the pixel types passed to it will give an error message as the original poster of this thread got.

HTH,
Brad

> On Jul 5, 2016, at 9:37 PM, Mathew Guilfoyle <mrguilfoyle at gmail.com> wrote:
> 
> Ziv: thanks for the reply.
> 
> I'm using the R wrapped version of SimpleITK
> 
> I've run the equivalent of your example:
> 
> library('SimpleITK')
> image = ReadImage('training_001_ct.mha')
> 
> segmented_image = image>700
> 
> lisf = LabelIntensityStatisticsImageFilter()
> lisf$Execute(segmented_image, image)
> 
> Unfortunately I'm getting the same error as for my own scripts:
> 
> Warning message:
> In f(...) :
>  Exception thrown in SimpleITK Show: /ITK/SITK/Source-Current/Build-290516/ITK-prefix/include/ITK-4.10/itkImageFileWriter.hxx:290:
> itk::ERROR: ImageFileWriter(0x10c05cbc0): Largest possible region does not fully contain requested paste IO regionPaste IO region: ImageIORegion (0x7fff5fbf6cd8)
>  Dimension: 2
>  Index: 0 0 
>  Size: 0 0 
> Largest possible region: ImageRegion (0x7fff5fbf6d70)
>  Dimension: 2
>  Index: [0, 0]
>  Size: [0, 0]
> 
> I have a feeling that this is a problem with the LabelIntensityStatisticsImageFilter being templated over 2D and 3D images and when it is instantiated it is defaulting to the 2D?  Previously using Python wrapped ITK (i.e. not SimpleITK) when I declared these filters I would give it a 2D or 3D image type but this is not possible in SimpleITK.
> 
> However, if this is working for you in Python-SimpleITK maybe it is an issue peculiar to the R wrapping?
> 
> Any further suggestions would be appreciated
> 
> Cheers
> 
>> On 5 Jul 2016, at 15:43, Yaniv, Ziv Rafael (NIH/NLM/LHC) [C] <zivrafael.yaniv at nih.gov> wrote:
>> 
>> Hi Mathew,
>> 
>> As I haven¹t seen your code I cannot pinpoint the issue, but it is not the
>> dimension of the image.
>> 
>> The following SimpleITK code does what I believe you are asking for (image
>> is available here - https://midas3.kitware.com/midas/item/317034):
>> 
>> import SimpleITK as sitk
>> 
>> image = sitk.ReadImage("training_001_ct.mha")
>> 
>> # HU values for bone are 700 and up
>> segmented_image = image>700
>> 
>> # segmented label for the threshold operation is 1 (0 for everything else).
>> # the LabelIntensityStatisticsImageFilter also works with multiple labels
>> and not just a binary segmentation.
>> segmented_label = 1
>> 
>> lisf = sitk.LabelIntensityStatisticsImageFilter()
>> lisf.Execute(segmented_image, image)
>> 
>> print("mean HU value: {0:.2f}".format(lisf.GetMean(segmented_label)))
>> 
>>    hope this helped
>> 
>>            Ziv
>> 
>> 
>> 
>> 
>> 
>> 
>> On 7/3/16, 9:11 PM, "Mathew Guilfoyle" <mrguilfoyle at gmail.com> wrote:
>> 
>>> Hi
>>> 
>>> Using SimpleITK I'm trying to get statistics for a grayscale image
>>> segmentation for which I have a binary mask.  Both image and mask are 3D
>>> volumes
>>> 
>>> I have converted my binary mask to a Label map and then tried to apply
>>> the LabelStatisticsImageFilter, however I get the following exception:
>>> 
>>> Pixel type: 32-bit float is not supported in 3D
>>> 
>>> I've tried casting the intensity image to unsigned int, Float 64 etc...
>>> none of them work.  It seems to be the 3D that is the issue.  Is this
>>> filter defined for 3D images?  There is nothing I have found in the
>>> documentation/source to suggest not.
>>> 
>>> Thanks
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> 
> _____________________________________
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> 
> Visit other Kitware open-source projects at
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> 
> Kitware offers ITK Training Courses, for more information visit:
> http://www.kitware.com/products/protraining.php
> 
> Please keep messages on-topic and check the ITK FAQ at:
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