def vtk_to_itk_image(key, vtk_image):
pixel_data = vtk_image['pointData']['values']
pixel_type = vtk_image['pointData']['dataType']
pixel_data = _vtkjs_type_convert(pixel_data, pixel_type)
# numpy indexes in ZYX order, where X varies the fastest
dims = [
vtk_image['extent'][5] - vtk_image['extent'][4] + 1,
vtk_image['extent'][3] - vtk_image['extent'][2] + 1,
vtk_image['extent'][1] - vtk_image['extent'][0] + 1,
]
direction = np.zeros((3, 3))
for x in range(3):
for y in range(3):
direction[x][y] = vtk_image['direction'][x * 3 + y]
itkImage = itk.GetImageFromArray(np.reshape(pixel_data, dims))
# https://discourse.itk.org/t/set-image-direction-from-numpy-array/844/10
vnlmat = itk.GetVnlMatrixFromArray(direction)
itkImage.GetDirection().GetVnlMatrix().copy_in(vnlmat.data_block())
itkImage.SetOrigin(vtk_image['origin'])
itkImage.SetSpacing(vtk_image['spacing'])
return itkImage
def read_3d_dicom(dicomFile, flip=False):
"""
Read dicom file and return an float 3D image
"""
files = []
files.append(pydicom.read_file(dicomFile[0]))
# skip files with no SliceLocation (eg scout views)
slices = []
if len(files) == 1:
slices.append(files[0])
else:
logger.error('no file available')
return
dicomProperties = dicom_properties()
dicomProperties.read_dicom_properties(slices[0])
# create 3D array
if len(slices[0].pixel_array.shape) == 2:
dicomProperties.img_shape = [1] + dicomProperties.img_shape
img3d = np.zeros(dicomProperties.img_shape)
# fill 3D array with the images from the files
if len(slices[0].pixel_array.shape) == 2:
img3d[0, :, :] = slices[0].pixel_array
else:
img3d[:, :, :] = slices[0].pixel_array
img3d = dicomProperties.rs * img3d + dicomProperties.ri
img_result = itk.image_from_array(np.float32(img3d))
img_result.SetSpacing(dicomProperties.spacing)
img_result.SetOrigin(dicomProperties.origin)
arrayDirection = np.zeros([3, 3], np.float64)
arrayDirection[0, 0] = dicomProperties.io[0]
arrayDirection[0, 1] = dicomProperties.io[1]
arrayDirection[0, 2] = dicomProperties.io[2]
arrayDirection[1, 0] = dicomProperties.io[3]
arrayDirection[1, 1] = dicomProperties.io[4]
arrayDirection[1, 2] = dicomProperties.io[5]
arrayDirection[2, :] = np.cross(arrayDirection[0, :], arrayDirection[1, :])
if Tag(0x18, 0x88) in slices[0] and slices[0][0x18, 0x88].value < 0:
arrayDirection[2, 2] = -1.0
else:
flip = False
arrayDirection[2, 2] = 1.0
matrixItk = itk.Matrix[itk.D, 3,
3](itk.GetVnlMatrixFromArray(arrayDirection))
img_result.SetDirection(matrixItk)
if flip:
flipFilter = itk.FlipImageFilter.New(Input=img_result)
flipFilter.SetFlipAxes((False, False, True))
flipFilter.SetFlipAboutOrigin(False)
flipFilter.Update()
img_result = flipFilter.GetOutput()
return img_result
def vtkjs_to_itk_image(vtkObject):
if vtkObject['vtkClass'] == 'vtkImageData':
imgArr = vtkObject['pointData']['arrays'][0]['data']['values']
# numpy indexes in ZYX order, where X varies the fastest
dims = [
vtkObject['extent'][5] - vtkObject['extent'][4] + 1,
vtkObject['extent'][3] - vtkObject['extent'][2] + 1,
vtkObject['extent'][1] - vtkObject['extent'][0] + 1,
]
direction = np.zeros((3, 3))
# why the direction is a json object instead of an array, nobody knows...
# (actually I think it's b/c "direction" is stored as a Float32Array in vtkjs)
for x in range(3):
for y in range(3):
direction[x][y] = vtkObject['direction'][str(x * 3 + y)]
itkImage = itk.GetImageFromArray(np.reshape(imgArr, dims))
# https://discourse.itk.org/t/set-image-direction-from-numpy-array/844/10
vnlmat = itk.GetVnlMatrixFromArray(direction)
itkImage.GetDirection().GetVnlMatrix().copy_in(vnlmat.data_block())
itkImage.SetOrigin(vtkObject['origin'])
itkImage.SetSpacing(vtkObject['spacing'])
return itkImage
return None
assert v1.get(0) == view[0] view[0] = 0 assert v1.get(0) == view[0] # VNL Matrices m1 = itk.vnl_matrix.D(2, 2) m1.fill(1) m_np = itk.GetArrayFromVnlMatrix(m1) assert m1.get(0, 0) == m_np[0, 0] m_np[0, 0] = 0 assert m1.get(0, 0) != m_np[0, 0] view = itk.GetArrayViewFromVnlMatrix(m1) assert m1.get(0, 0) == view[0, 0] view[0, 0] = 0 assert m1.get(0, 0) == view[0, 0] arr = np.zeros([3, 3]) m_vnl = itk.GetVnlMatrixFromArray(arr) assert m_vnl(0, 0) == 0 m_vnl.put(0, 0, 3) assert m_vnl(0, 0) == 3 assert arr[0, 0] == 0 # ITK Matrix arr = np.zeros([3, 3], float) m_itk = itk.GetMatrixFromArray(arr) # Test snake case function m_itk = itk.matrix_from_array(arr) m_itk.SetIdentity() # Test that the numpy array has not changed,... assert arr[0, 0] == 0 # but that the ITK matrix has the correct value. assert m_itk(0, 0) == 1 arr2 = itk.GetArrayFromMatrix(m_itk)
np_copy = itk.GetArrayFromImage(itk_image) #do numpy stuff #convert back to itk, view only, data is not copied itk_np_view = itk.GetImageViewFromArray(np_copy) #convert back to itk, data is not copied itk_np_copy = itk.GetImageFromArray(np_copy) # Save result itk.imwrite(itk_np_view, output_filename) # Vnl matrix[View] from array arr = np.zeros([3, 3], np.uint8) matrix_view = itk.GetVnlMatrixViewFromArray(arr) matrix = itk.GetVnlMatrixFromArray(arr) # Array[View] from Vnl matrix arr_view = itk.GetArrayViewFromVnlMatrix(matrix) arr = itk.GetArrayFromVnlMatrix(matrix) # Vnl vector[View] from array vec = np.zeros([3], np.uint8) vnl_vector_view = itk.GetVnlVectorViewFromArray(vec) vnl_vector = itk.GetVnlVectorFromArray(vec) # Array[View] from Vnl vector vec_view = itk.GetArrayViewFromVnlVector(vnl_vector) vec = itk.GetArrayFromVnlVector(vnl_vector)
def read_dicom(dicomFiles):
"""
Read dicom files and return an float 3D image
"""
files = []
#Load dicom files
for file in dicomFiles:
try:
files.append(pydicom.read_file(file))
except pydicom.errors.InvalidDicomError:
ds = pydicom.read_file(file, force=True)
ds.file_meta.TransferSyntaxUID = pydicom.uid.ImplicitVRLittleEndian
files.append(ds)
# skip files with no SliceLocation (eg scout views)
slices = []
skipcount = 0
if len(files) > 1:
for f in files:
if hasattr(f, 'SliceLocation') or hasattr(f,
'ImagePositionPatient'):
slices.append(f)
else:
skipcount = skipcount + 1
if skipcount > 0:
logger.info("skipped, no SliceLocation: {}".format(skipcount))
# ensure they are in the correct order. Sort according Image Position along z
slices = sorted(slices, key=lambda s: s[0x0020, 0x0032][2])
else:
logger.error('no file available')
return
if len(slices) == 0:
logger.error('no slice available')
return
dicomProperties = dicom_properties()
if len(slices) >= 2:
dicomProperties.read_dicom_properties(slices[0], slices[1])
else:
dicomProperties.read_dicom_properties(slices[0])
# create 3D array
dicomProperties.img_shape[0] = len(slices)
dicomProperties.img_shape.append(slices[0].pixel_array.shape[0])
img3d = np.zeros(dicomProperties.img_shape)
# fill 3D array with the images from the files
for i, s in enumerate(slices):
img2d = s.pixel_array
dicomPropertiesSlice = dicom_properties()
dicomPropertiesSlice.read_dicom_slop_intercept(s)
img3d[
i, :, :] = dicomPropertiesSlice.rs * img2d + dicomPropertiesSlice.ri
img_result = itk.image_from_array(np.float32(img3d))
img_result.SetSpacing(dicomProperties.spacing)
img_result.SetOrigin(dicomProperties.origin)
arrayDirection = np.zeros([3, 3], np.float64)
arrayDirection[0, 0] = dicomProperties.io[0]
arrayDirection[0, 1] = dicomProperties.io[1]
arrayDirection[0, 2] = dicomProperties.io[2]
arrayDirection[1, 0] = dicomProperties.io[3]
arrayDirection[1, 1] = dicomProperties.io[4]
arrayDirection[1, 2] = dicomProperties.io[5]
arrayDirection[2, :] = np.cross(arrayDirection[0, :], arrayDirection[1, :])
matrixItk = itk.Matrix[itk.D, 3,
3](itk.GetVnlMatrixFromArray(arrayDirection))
img_result.SetDirection(matrixItk)
return img_result
def main(args):
if (args.json):
imgs_arr = []
for img_index, img_filename in enumerate(args.img):
img_read = itk.ImageFileReader.New(FileName=img_filename)
img_read.Update()
img = img_read.GetOutput()
imgs_arr.append(img)
description_arr = []
with open(args.json, "r") as jsf:
description_arr = json.load(jsf)
for img in imgs_arr:
img_np = itk.GetArrayViewFromImage(img)
for img_index in range(img_np.shape[0]):
description = description_arr[img_index]
RegionType = itk.ImageRegion[2]
region = RegionType()
region.SetIndex(description["image"]["region"]["index"])
region.SetSize(description["image"]["region"]["size"])
PixelType = itk.template(img)[1][0]
OutputImageType = itk.Image[PixelType, 2]
out_img = OutputImageType.New()
out_img.SetRegions(region)
out_img.SetOrigin(description["image"]["origin"])
out_img.SetSpacing(description["image"]["spacing"])
np_dir_vnl = itk.GetVnlMatrixFromArray(
np.array(description["image"]["direction"]))
direction = out_img.GetDirection()
direction.GetVnlMatrix().copy_in(np_dir_vnl.data_block())
out_img.Allocate()
out_img_np = itk.GetArrayViewFromImage(out_img)
out_img_np.setfield(img_np[img_index], out_img_np.dtype)
if (not os.path.exists(args.out)
or not os.path.isdir(args.out)):
os.makedirs(args.out)
out_filename = os.path.join(args.out,
description["img_filename"])
print("Writing:", out_filename)
writer = itk.ImageFileWriter.New(FileName=out_filename,
Input=out_img)
writer.Update()
else:
imgs_arr = []
imgs_arr_description = []
csv_headers = []
if args.out_csv_headers:
csv_headers = args.out_csv_headers
for img_index, img_filename in enumerate(args.img):
img_read = itk.ImageFileReader.New(FileName=img_filename)
img_read.Update()
img = img_read.GetOutput()
imgs_arr.append(img)
if args.out_csv_headers is None:
csv_headers.append(img_index)
img_obj_description = {}
img_obj_description["image"] = {}
img_obj_description["image"]["region"] = {}
img_obj_description["image"]["region"]["size"] = np.array(
img.GetLargestPossibleRegion().GetSize()).tolist()
img_obj_description["image"]["region"]["index"] = np.array(
img.GetLargestPossibleRegion().GetIndex()).tolist()
img_obj_description["image"]["spacing"] = np.array(
img.GetSpacing()).tolist()
img_obj_description["image"]["origin"] = np.array(
img.GetOrigin()).tolist()
img_obj_description["image"][
"direction"] = itk.GetArrayFromVnlMatrix(
img.GetDirection().GetVnlMatrix().as_matrix()).tolist()
img_obj_description["img_index"] = img_index
img_obj_description["img_filename"] = img_filename
img_obj_description["slice"] = {}
imgs_arr_description.append(img_obj_description)
if len(args.img) != len(csv_headers):
print(
"The csv headers provided do not have the same length as the number of images provided",
file=sys.stderr)
sys.exit(1)
if len(imgs_arr) == 0:
print("You need to provide at least one image!", file=sys.stderr)
sys.exit(1)
print(imgs_arr_description)
img_np = itk.GetArrayViewFromImage(imgs_arr[0])
img_shape_max = np.max(img_np.shape)
out_size = np.array([img_shape_max, img_shape_max]).tolist()
PixelType = itk.template(imgs_arr[0])[1][0]
OutputImageType = itk.Image[PixelType, 2]
out_csv_rows = []
if imgs_arr[0].GetImageDimension() == 3:
img_shape = img_np.shape
for dim in range(imgs_arr[0].GetImageDimension()):
imgs_arr_description[img_index]["slice"][dim] = []
for sln in range(img_shape[dim]):
start = [0, 0, 0]
end = [None, None, None]
start[dim] = sln
end[dim] = sln + 1
uuid_out_name = str(uuid.uuid4())
out_obj_csv = {}
for img_index, img in enumerate(imgs_arr):
img_np = itk.GetArrayViewFromImage(img)
img_np_2d = np.squeeze(img_np[start[0]:end[0],
start[1]:end[1],
start[2]:end[2]],
axis=dim)
size_np = img_np_2d.shape
img_np_2d_max_size = np.zeros(out_size)
img_np_2d_max_size[0:size_np[0],
0:size_np[1]] = img_np_2d
index = itk.Index[2]()
index.Fill(0)
RegionType = itk.ImageRegion[2]
region = RegionType()
region.SetIndex(index)
region.SetSize(out_size)
out_img = OutputImageType.New()
out_img.SetRegions(region)
out_img.SetOrigin(
np.delete(img.GetOrigin(), dim).tolist())
out_img.SetSpacing(
np.delete(img.GetSpacing(), dim).tolist())
out_img.Allocate()
out_img_np = itk.GetArrayViewFromImage(out_img)
out_img_np.setfield(img_np_2d_max_size,
out_img_np.dtype)
out_dir = os.path.join(args.out,
str(csv_headers[img_index]))
if (not os.path.exists(out_dir)
or not os.path.isdir(out_dir)):
os.makedirs(out_dir)
out_filename = os.path.join(out_dir,
uuid_out_name + ".nrrd")
print("Writing:", out_filename)
writer = itk.ImageFileWriter.New(FileName=out_filename,
Input=out_img)
writer.Update()
out_obj_csv[csv_headers[img_index]] = out_filename
imgs_arr_description[img_index]["slice"][dim].append(
out_filename)
out_csv_rows.append(out_obj_csv)
with open(args.out_csv, "w") as f:
writer = csv.DictWriter(f, fieldnames=csv_headers)
writer.writeheader()
for row in out_csv_rows:
writer.writerow(row)
if (args.json_desc):
with open(args.json_desc, "w") as f:
f.write(json.dumps(imgs_arr_description))
