def test_is_multiframe_4d(self):
assert convert_philips._is_multiframe_4d(read_dicom_directory(test_data.PHILIPS_ENHANCED_DTI))
assert not convert_philips._is_multiframe_4d(read_dicom_directory(test_data.PHILIPS_DTI))
assert not convert_philips._is_multiframe_4d(read_dicom_directory(test_data.PHILIPS_ENHANCED_ANATOMICAL))
assert not convert_philips._is_multiframe_4d(read_dicom_directory(test_data.PHILIPS_ANATOMICAL))
assert convert_philips._is_multiframe_4d(read_dicom_directory(test_data.PHILIPS_ENHANCED_FMRI))
assert not convert_philips._is_multiframe_4d(read_dicom_directory(test_data.PHILIPS_FMRI))
def shrink_multiframe(input_file, output_file=None, slice_count=8, timepoint_count=4):
if output_file is None:
output_file = input_file
# Load dicom_file_in
dicom_in = compressed_dicom.read_file(input_file)
if _is_multiframe_diffusion_imaging([dicom_in]) or _is_multiframe_4d([dicom_in]):
number_of_stack_slices = int(common.get_ss_value(dicom_in[(0x2001, 0x105f)][0][(0x2001, 0x102d)]))
number_of_stacks = int(int(dicom_in.NumberOfFrames) / number_of_stack_slices)
# We create a numpy array
size_x = dicom_in.pixel_array.shape[2]
size_y = dicom_in.pixel_array.shape[1]
size_t = number_of_stacks
frame_info = dicom_in.PerFrameFunctionalGroupsSequence
data_4d = numpy.zeros((slice_count * timepoint_count, size_x, size_y), dtype=common.get_numpy_type(dicom_in))
new_frame_info = [None] * slice_count * timepoint_count
for index_z in range(0, slice_count):
for index_t in range(0, timepoint_count):
slice_index = int(size_t * index_z + index_t)
new_slice_index = int(timepoint_count * index_z + index_t)
z_location = frame_info[slice_index].FrameContentSequence[0].InStackPositionNumber - 1
new_frame_info[new_slice_index] = frame_info[slice_index]
logging.info('Importing slice on position %s %s %s' % (slice_index, z_location, index_t))
data_4d[new_slice_index, :, :] = dicom_in.pixel_array[slice_index, :, :]
dicom_in.PixelData = data_4d.tostring()
common.set_ss_value(dicom_in[(0x2001, 0x105f)][0][(0x2001, 0x102d)], slice_count)
setattr(dicom_in, 'NumberOfFrames', slice_count * timepoint_count)
setattr(dicom_in, 'PerFrameFunctionalGroupsSequence', new_frame_info)
else:
# truncate the data
dicom_in.PixelData = dicom_in.pixel_array[:slice_count, :, :].tostring()
# set number of frames
common.set_ss_value(dicom_in[(0x2001, 0x105f)][0][(0x2001, 0x102d)], slice_count)
setattr(dicom_in, 'NumberOfFrames', slice_count)
# truncate the pre frame groups sequence
setattr(dicom_in, 'PerFrameFunctionalGroupsSequence', dicom_in.PerFrameFunctionalGroupsSequence[:slice_count])
# Save the file
dicom_in.save_as(output_file)
def test_is_multiframe_4d(self):
assert convert_philips._is_multiframe_4d(
read_dicom_directory(test_data.PHILIPS_ENHANCED_DTI))
assert not convert_philips._is_multiframe_4d(
read_dicom_directory(test_data.PHILIPS_DTI))
assert not convert_philips._is_multiframe_4d(
read_dicom_directory(test_data.PHILIPS_ENHANCED_ANATOMICAL))
assert not convert_philips._is_multiframe_4d(
read_dicom_directory(test_data.PHILIPS_ANATOMICAL))
assert convert_philips._is_multiframe_4d(
read_dicom_directory(test_data.PHILIPS_ENHANCED_FMRI))
assert not convert_philips._is_multiframe_4d(
read_dicom_directory(test_data.PHILIPS_FMRI))
def shrink_multiframe(input_file,
output_file=None,
slice_count=8,
timepoint_count=4):
if output_file is None:
output_file = input_file
# Load dicom_file_in
dicom_in = compressed_dicom.read_file(input_file)
if _is_multiframe_diffusion_imaging([dicom_in]) or _is_multiframe_4d(
[dicom_in]):
number_of_stack_slices = int(
common.get_ss_value(dicom_in[(0x2001, 0x105f)][0][(0x2001,
0x102d)]))
number_of_stacks = int(
int(dicom_in.NumberOfFrames) / number_of_stack_slices)
# We create a numpy array
size_x = dicom_in.pixel_array.shape[2]
size_y = dicom_in.pixel_array.shape[1]
size_t = number_of_stacks
frame_info = dicom_in.PerFrameFunctionalGroupsSequence
data_4d = numpy.zeros((slice_count * timepoint_count, size_x, size_y),
dtype=common.get_numpy_type(dicom_in))
new_frame_info = [None] * slice_count * timepoint_count
for index_z in range(0, slice_count):
for index_t in range(0, timepoint_count):
slice_index = int(size_t * index_z + index_t)
new_slice_index = int(timepoint_count * index_z + index_t)
z_location = frame_info[slice_index].FrameContentSequence[
0].InStackPositionNumber - 1
new_frame_info[new_slice_index] = frame_info[slice_index]
logging.info('Importing slice on position %s %s %s' %
(slice_index, z_location, index_t))
data_4d[new_slice_index, :, :] = dicom_in.pixel_array[
slice_index, :, :]
dicom_in.PixelData = data_4d.tostring()
common.set_ss_value(dicom_in[(0x2001, 0x105f)][0][(0x2001, 0x102d)],
slice_count)
setattr(dicom_in, 'NumberOfFrames', slice_count * timepoint_count)
setattr(dicom_in, 'PerFrameFunctionalGroupsSequence', new_frame_info)
else:
# truncate the data
dicom_in.PixelData = dicom_in.pixel_array[:slice_count, :, :].tostring(
)
# set number of frames
common.set_ss_value(dicom_in[(0x2001, 0x105f)][0][(0x2001, 0x102d)],
slice_count)
setattr(dicom_in, 'NumberOfFrames', slice_count)
# truncate the pre frame groups sequence
setattr(dicom_in, 'PerFrameFunctionalGroupsSequence',
dicom_in.PerFrameFunctionalGroupsSequence[:slice_count])
# Save the file
dicom_in.save_as(output_file)