def generate_filename_list(folder,
file_regex='*.nii*',
labels=False,
label_suffix='-label',
set_label='',
recursive=False):
if recursive:
imagepaths = grab_files_recursive(folder, file_regex)
else:
imagepaths = glob.glob(os.path.join(folder, file_regex))
if labels:
if set_label == '':
label_images = [x for x in imagepaths if label_suffix in x]
imagepaths = [x for x in imagepaths if label_suffix not in x]
else:
label_images = [
os.path.join(os.path.dirname(x), os.path.basename(set_label))
if os.path.exists(x) else '' for x in imagepaths
]
imagepaths = [
x for x in imagepaths if os.path.join(
os.path.dirname(x), os.path.basename(set_label)) not in x
]
else:
label_images = []
if imagepaths == []:
raise ValueError(
"There are no .nii or .nii.gz images in the provided folder.")
if labels and label_images == []:
raise ValueError(
"There are no labels with the provided suffix in this folder. If you do not want to use labels, set the \'labels\' flag to \'False\'. If you want to change the label file suffix (default: \'-label\'), then change the \'label_suffix\' flag."
)
return [imagepaths, label_images]
def dcm_2_numpy(input_folder, verbose=False):
""" Uses pydicom to stack an alphabetical list of DICOM files. TODO: Make it
take slice_order into account.
"""
if verbose:
print('Searching for dicom files...')
found_files = grab_files_recursive(input_folder)
if verbose:
print('Found', len(found_files), 'in directory. \n')
print('Checking DICOM compatability...')
dicom_files = []
for file in found_files:
try:
temp_dicom = pydicom.read_file(file)
dicom_files += [[
file, temp_dicom.data_element('SeriesInstanceUID').value
]]
except:
continue
if verbose:
print('Found', len(dicom_files), 'DICOM files in directory. \n')
print('Counting volumes..')
unique_dicoms = defaultdict(list)
for dicom_file in dicom_files:
UID = dicom_file[1]
unique_dicoms[UID] += [dicom_file[0]]
if verbose:
print('Found', len(list(unique_dicoms.keys())), 'unique volumes \n')
print('Saving out files from these volumes.')
output_dict = {}
output_filenames = []
for UID in list(unique_dicoms.keys()):
try:
# Grab DICOMs for a certain Instance
current_files = unique_dicoms[UID]
current_dicoms = [
get_uncompressed_dicom(dcm) for dcm in unique_dicoms[UID]
]
# print current_files
# Sort DICOMs by Instance.
dicom_instances = [
x.data_element('InstanceNumber').value for x in current_dicoms
]
current_dicoms = [
x for _, x in sorted(zip(dicom_instances, current_dicoms))
]
current_files = [
x for _, x in sorted(zip(dicom_instances, current_files))
]
first_dicom, last_dicom = current_dicoms[0], current_dicoms[-1]
print(first_dicom.file_meta)
print(first_dicom.file_meta.TransferSyntaxUID)
# Create a filename for the DICOM
volume_label = '_'.join([
first_dicom.data_element(tag).value for tag in naming_tags
]).replace(" ", "")
volume_label = prefix + sanitize_filename(
volume_label) + suffix + '.nii.gz'
if verbose:
print('Saving...', volume_label)
except:
print(
'Could not read DICOM volume SeriesDescription. Skipping UID...',
str(UID))
continue
try:
# Extract patient position information for affine creation.
output_affine = np.eye(4)
image_position_patient = np.array(
first_dicom.data_element('ImagePositionPatient').value).astype(
float)
image_orientation_patient = np.array(
first_dicom.data_element(
'ImageOrientationPatient').value).astype(float)
last_image_position_patient = np.array(
last_dicom.data_element('ImagePositionPatient').value).astype(
float)
pixel_spacing_patient = np.array(
first_dicom.data_element('PixelSpacing').value).astype(float)
# Create DICOM Space affine (don't fully understand, TODO)
output_affine[
0:3,
0] = pixel_spacing_patient[0] * image_orientation_patient[0:3]
output_affine[
0:3,
1] = pixel_spacing_patient[1] * image_orientation_patient[3:6]
output_affine[
0:3,
2] = (image_position_patient -
last_image_position_patient) / (1 - len(current_dicoms))
output_affine[0:3, 3] = image_position_patient
# Transformations from DICOM to Nifti Space (don't fully understand, TOO)
cr_flip = np.eye(4)
cr_flip[0:2, 0:2] = [[0, 1], [1, 0]]
neg_flip = np.eye(4)
neg_flip[0:2, 0:2] = [[-1, 0], [0, -1]]
output_affine = np.matmul(neg_flip,
np.matmul(output_affine, cr_flip))
# Create numpy array data...
output_shape = get_dicom_pixel_array(current_dicoms[0],
current_files[0]).shape
output_numpy = []
for i in range(len(current_dicoms)):
try:
output_numpy += [
get_dicom_pixel_array(current_dicoms[i],
current_files[i])
]
except:
print('Warning, error at slice', i)
output_numpy = np.stack(output_numpy, -1)
# If preferred, harden to identity matrix space (LPS, maybe?)
# Also unsure of the dynamic here, but they work.
if harden_orientation is not None:
cx, cy, cz = np.argmax(np.abs(output_affine[0:3, 0:3]), axis=0)
output_numpy = np.transpose(output_numpy, (cx, cy, cz))
harden_matrix = np.eye(4)
for dim, i in enumerate([cx, cy, cz]):
harden_matrix[i, i] = 0
harden_matrix[dim, i] = 1
output_affine = np.matmul(output_affine, harden_matrix)
flip_matrix = np.eye(4)
for i in range(3):
if output_affine[i, i] < 0:
flip_matrix[i, i] = -1
output_numpy = np.flip(output_numpy, i)
output_affine = np.matmul(output_affine, flip_matrix)
# Create output folder according to tags.
specific_folder = output_folder
for tag in folder_tags:
if specific_folder == output_folder or folder_mode == 'recursive':
specific_folder = os.path.join(
specific_folder,
sanitize_filename(first_dicom.data_element(tag).value))
elif folder_mode == 'combine':
specific_folder = specific_folder + '_' + sanitize_filename(
first_dicom.data_element(tag).value)
if not os.path.exists(specific_folder):
os.makedirs(specific_folder)
# Save out file.
output_filename = os.path.join(specific_folder, volume_label)
if os.path.exists(
output_filename) and output_filename in output_filenames:
output_filename = replace_suffix(output_filename, '', '_copy')
save_numpy_2_nifti(output_numpy, output_affine, output_filename)
output_filenames += [output_filename]
except:
print('Could not read DICOM at SeriesDescription...', volume_label)
return output_filenames
return output_dict