HDF5Datas = []
HDF5Labels = []
# Read reference image
ReferenceName = args.reference[i]
print '================================================================'
print 'Processing image : ', ReferenceName
# Read NIFTI
ReferenceNifti = sitk.ReadImage(ReferenceName)
# Get data from NIFTI
ReferenceImage = np.swapaxes(sitk.GetArrayFromImage(ReferenceNifti), 0,
2).astype('float32')
# Normalization
ReferenceImage = imadjust3D(ReferenceImage, [0, 1])
# ===== Generate input LR image =====
# Blurring
BlurReferenceImage = scipy.ndimage.filters.gaussian_filter(
ReferenceImage, sigma=args.sigma)
for scale in args.scale:
print 'With respect to scale factor x', scale, ' : '
# Modcrop to scale factor
BlurReferenceImage = modcrop3D(BlurReferenceImage, scale)
ReferenceImage = modcrop3D(ReferenceImage, scale)
# Downsampling
LowResolutionImage = scipy.ndimage.zoom(
print '================================================================'
print 'Processing (label) reference image : ', ReferenceName
print 'Processing input image : ', InputName
# Read NIFTI
ReferenceNifti = sitk.ReadImage(ReferenceName)
InputNifti = sitk.ReadImage(InputName)
# Get data from NIFTI
ReferenceImage = np.swapaxes(sitk.GetArrayFromImage(ReferenceNifti), 0,
2).astype('float32')
InputImage = np.swapaxes(sitk.GetArrayFromImage(InputNifti), 0,
2).astype('float32')
# Normalization
ReferenceImage = imadjust3D(ReferenceImage, [0, 1])
InputImage = imadjust3D(InputImage, [0, 1])
# Compute scale factor:
TargetShape = ReferenceImage.shape
InputShape = InputImage.shape
scale = (Targetidx / inputidx
for Targetidx, inputidx in zip(TargetShape, InputShape))
print 'With respect to scale factor x', scale
# Cubic Interpolation
if TargetShape != InputShape:
InputImage = scipy.ndimage.zoom(InputImage,
zoom=scale,
order=args.order)
print '================================================================'
print 'Processing image : ', ReferenceName
print 'Intermodality image : ', IntermodalityName
# Read NIFTI
ReferenceNifti = sitk.ReadImage(ReferenceName)
IntermodalityNifti = sitk.ReadImage(IntermodalityName)
# Get data from NIFTI
ReferenceImage = np.swapaxes(sitk.GetArrayFromImage(ReferenceNifti), 0,
2).astype('float32')
IntermodalityImage = np.swapaxes(
sitk.GetArrayFromImage(IntermodalityNifti), 0, 2).astype('float32')
# Normalization
ReferenceImage = imadjust3D(ReferenceImage, [0, 1])
IntermodalityImage = imadjust3D(IntermodalityImage, [0, 1])
# ===== Generate input LR image =====
# Blurring
BlurReferenceImage = scipy.ndimage.filters.gaussian_filter(
ReferenceImage, sigma=args.sigma)
for scale in args.scale:
print 'With respect to scale factor x', scale, ' : '
# Modcrop to scale factor
BlurReferenceImage = modcrop3D(BlurReferenceImage, scale)
ReferenceImage = modcrop3D(ReferenceImage, scale)
# Downsampling