[Neuroimaging] [DiPy] Registration problem integer image arrays

[Bene Wiestler]

Hi Pietro,

thanks for your reply. In fact, this is exactly my workflow. However, 
when I call the .transform-method of c_of_mass, the result is an 
all-zero array (both with interp="linear" or "nearest").

Cheers,

Bene

Pietro Astolfi wrote:
> Hi,
> 
> You can use uint16 for both the images when you load them. Then if the images are nifti files you don’t need to transform them to array, you should use the class method .get_data() to extract the numpy array from the loaded image. I give you a practice working example with c_of_mass:
> 
> import nibabel as nib
> import numpy as np
> from dipy.align.imaffine import transform_centers_of_mass
> 
> # static image
> img1 = nib.load(‘img1.nii.gz’)
> img1_data = img1.get_data() #now img1_data is a numpy array of float
> img1_data = img1_data.as_type(np.uint16)
> aff1 = img1.affine
> 
> # moving image
> img2 = nib.load(‘img2.nii.gz’)
> img2_data = img2.get_data() #now img2_data is a numpy array of float
> img2_data = img2_data.as_type(np.uint16)
> aff2 = img2.affine
> 
> c_of_mass = transform_centers_of_mass(img1_data, aff1, img2_data, aff2)
> 
> transformed = c_of_mass.transform(img2_data) # note that transform function cast the input array (img2_data here) as np.float64 in order to interpolate, so the returned array (transformed here) is a float64
> 
> let me know if this helps you.
> 
> Pietro
> 
>> Il giorno 03 mag 2018, alle ore 09:04, Bene Wiestler <b.wiestler at tum.de> ha scritto:
>>
>> Hi,
>>
>> I have a problem with the dipy image registration workflow:
>> I want to register two anatomical images using linear methods (c_of_mass, translation, rigid). One file is a uint16 data type, the other is saved as a float, however essentially also only contains integer. When I load these files with nibabel and convert the data arrays to int16 (both with the .astype(np-int16) methods and with numpy.asarray), registration (even c_of_mass) always yields an empty transformed moving image (i.e. just containing 0s). However, when I save the files using the converted int16 data arrays and open them in e.g. ITK-Snap, they look fine.
>> When I convert both files to float32, registration works, but is slow.
>> Further, when I run your example script for affine registration with the files provided there (Stanford; syn; both int16), it works fine for these files.
>> Has anybody any idea what might be a solution other than just float32?
>>
>> Thanks a lot!
>>
>> Bene
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> 


-- 
Dr. med. Benedikt Wiestler
Abteilung für Neuroradiologie
Klinikum rechts der Isar, TU München
Ismaninger Str. 22
81675 München
goo.gl/178PRF