I have two 3D images (creat from 2 different registration methods, 2 images with same size (476,512,512) origin (0,0,0), direction(1,0,0,0,1,0,0,0,1)). I visualized 2 images with matplotlib (same slice) and got the the views as following.
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize = (20, 10))
ax1.imshow(a[ 150, :, :],‘gray’)
ax2.imshow(a[ :, 256, :], ‘gray’)
ax3.imshow(a[ :, :, 200], ‘gray’)
It seems that image A and B have different views (axial, coronal and diggital) (and flip axis?). I want to convert the views of B to be the same as A. Could you please suggest what I might try?
Many thanks,
If the images have the same size origin and direction, the axial, sagittal and coronal views should match (possibly rotated).
Based on the provided size (476,512,512) you are looking at a numpy array and not the original SimpleITK image. Note that the index order in SimpleITK and numpy is reversed, image[x,y,z] vs. image_numpy_array[z,y,x]. Possibly the two are mixed resulting in the mismatch.
