[ITK-users] [ITK] SimpleITK, read MHD volume and convert it into a numpy array respecting its transformation
Paolo Zaffino
p.zaffino at yahoo.it
Wed May 4 15:36:07 EDT 2016
Hi Fausto,
if you want to accomplish all the stuff entirely from the scipy/scikit
side, I think you could use [1] and [2] (check the matching between
documentation version and library version).
HTH.
Best.
Paolo
[1]
http://docs.scipy.org/doc/scipy-0.16.0/reference/generated/scipy.ndimage.interpolation.rotate.html
[2]
http://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.rotate
On 04/05/2016 20:40, fausto milletarì 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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>
>
>
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