[ITK] [ITK-users] SimpleITK, read MHD volume and convert it into a numpy array respecting its transformation

[fausto milletarì]

Hello,

just as a brief attempt i tried:
resample=sitk.ResampleImageFilter()
resample.SetReferenceImage(img)
resample.SetOutputDirection(img.GetDirection())
Seems that, after I obtain the numpy array as: 
test=resample.Execute(img)
volume=sitk.GetArrayFromImage(test)
Nothing changes in terms of data array.
If I also add resample.SetOutputSpacing(img.GetSpacing()/2.) then the numpy array changes and depicts a down-sampled version of the image.
I suspect i have to use resample.SetTransform() but I will need to create this transform using one of the transform types available in sitk. How can I create a transform that is equivalent to the one contained in the header of my MHD file? Should I create a transform starting from the volume direction and maybe offset? I could not find any example of this so far…

Best regards and thanks much for your help and your answers,
Fausto 





> On 04 May 2016, at 20:40, fausto milletarì <fausto.milletari at gmail.com> wrote:
> 
> Hello, 
> 
> I thank you for you fast and accurate answer. This was exactly what I was looking for. Actually I don’t need to visualise the data but further process it in a common reference frame. I think that your answer solves the problem. I will look into the ResampleImageFilter (that so far I was using only to adjust the resolution of different volumes acquired with different scanners to a common one).
> 
> 
> Thanks a lot!
> 
> Fausto Milletari
>> On 04 May 2016, at 20:36, Lowekamp, Bradley (NIH/NLM/LHC) [C] <blowekamp at mail.nih.gov <mailto:blowekamp at mail.nih.gov>> wrote:
>> 
>> Hello,
>> 
>> If I understand you correctly you want to rotate the image and pad it for visualization before exporting to numpy.
>> 
>> Have you looked into the ResampleImageFilter? It accepts a transform, along with output image geometry so that you can readily manipulate the image for display. You also may want to scale the image’s intensity with a WindowLevelImageFilter for better visualization of the range of interest.
>> 
>> HTH,
>> Brad
>> 
>>> On May 4, 2016, at 1:14 PM, fausto milletarì <fausto.milletari at gmail.com <mailto:fausto.milletari at gmail.com>> wrote:
>>> 
>>> Hello everyone,
>>> 
>>> I have a probably naive question about simpleITK. I find simpleITK extremely useful to process medical data such as MRI scans but I would like also to enjoy being able to convert my images in numpy format while respecting the transformation of the volume.
>>> 
>>> In other words I would like to get the MRI image in numpy rotated by the correct amount around each axis with zero padding for example.
>>> 
>>> when i do simply sitk.GetArrayFromImage(imgResampledCropped)I get back the raw data itself, but what I would like to do is to have a numpy array that contains the data “ready to visualise” by simple slicing of the array itself.
>>> 
>>> Do you think this is doable? Is there a standard way of doing it?
>>> 
>>> 
>>> 
>>> Kind regards,
>>> 
>>> Fausto
>>> 
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