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

fausto milletarì fausto.milletari at gmail.com
Wed May 4 14:40:23 EDT 2016


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> 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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