def _load(self):
self.files = _get_files(self.file_dir, self.file_pattern)
self.stack = dicomSeries.read_files(self.files,
showProgress=True,
readPixelData=True)[0]
if HAS_GIAS:
self._make_scan()
def main():
args = getArguments(getParser())
# prepare logger
logger = Logger.getInstance()
if args.debug: logger.setLevel(logging.DEBUG)
elif args.verbose: logger.setLevel(logging.INFO)
# load dicom slices
[series] = pydicom_series.read_files(
args.input, False,
True) # second to not show progress bar, third to retrieve data
#print series.sampling # Note: The first value is the mean of all differences between ImagePositionPatient-values of the DICOM slices - of course total bullshit
data_3d = series.get_pixel_array()
# check parameters
if args.dimension >= data_3d.ndim or args.dimension < 0:
raise ArgumentError(
'The image has only {} dimensions. The supplied target dimension {} exceeds this number.'
.format(data_3d.ndim, args.dimension))
if not 0 == data_3d.shape[args.dimension] % args.offset:
raise ArgumentError(
'The number of slices {} in the target dimension {} of the image shape {} is not dividable by the supplied number of consecutive slices {}.'
.format(data_3d.shape[args.dimension], args.dimension,
data_3d.shape, args.offset))
# prepare empty target volume
volumes_3d = data_3d.shape[args.dimension] / args.offset
shape_4d = list(data_3d.shape)
shape_4d[args.dimension] = volumes_3d
data_4d = scipy.zeros([args.offset] + shape_4d, dtype=data_3d.dtype)
logger.debug(
'Separating {} slices into {} 3D volumes of thickness {}.'.format(
data_3d.shape[args.dimension], volumes_3d, args.offset))
# iterate over 3D image and create sub volumes which are then added to the 4d volume
for idx in range(args.offset):
# collect the slices
for sl in range(volumes_3d):
idx_from = [slice(None), slice(None), slice(None)]
idx_from[args.dimension] = slice(idx + sl * args.offset,
idx + sl * args.offset + 1)
idx_to = [slice(None), slice(None), slice(None)]
idx_to[args.dimension] = slice(sl, sl + 1)
#print 'Slice {} to {}.'.format(idx_from, idx_to)
data_4d[idx][idx_to] = data_3d[idx_from]
# flip dimensions such that the newly created is the last
data_4d = scipy.swapaxes(data_4d, 0, 3)
# save resulting 4D volume
save(data_4d, args.output, False, args.force)
logger.info("Successfully terminated.")
def get3DRecon(data, path):
"""
Performs 3D reconstruction from the given DICOM data, and
returns a voxel array and the pixel spacing factors.
"""
global ConstPixelSpacing
# del(data[0])
# RefDs = data[0]
# ConstPixelSpacing = (float(RefDs.PixelSpacing[0]), float(
# RefDs.PixelSpacing[1]), float(RefDs.SliceThickness))
series = pydicom_series.read_files(
path, False,
True) # second to not show progress bar, third to retrieve data
# print len(series)
voxel_ndarray = series[0].get_pixel_array()
print voxel_ndarray.shape
voxel_ndarray = series[1].get_pixel_array()
print voxel_ndarray.shape
voxel_ndarray = series[2].get_pixel_array()
print voxel_ndarray.shape
# print voxel_ndarray.shape
# assert False, "Stop"
# info = series[1].info
# try:
# voxel_ndarray, ijk_to_xyz = dicom_numpy.combine_slices(data)
# except dicom_numpy.DicomImportException as e:
# # Invalid DICOM data
# print("Handling incompatible dicom slices")
# # voxel_ndarray, ijk_to_xyz = dicom_numpy.combine_slices(data)
# try:
# # makeCompatible(data, prec=5)
# voxel_ndarray, ijk_to_xyz = dicom_numpy.combine_slices(data)
# except:
# print("Handling incompatible dicom slices")
# voxel_ndarray = []
# for i in range(len(data)):
# # print data[i].pixel_array.shape
# # assert False, "Stop Code"
# voxel_ndarray.append(data[i].pixel_array)
# voxel_ndarray = np.stack(voxel_ndarray, axis=2)
# # multi_slice_viewer(voxel_ndarray)
# # plt.show()
# ijk_to_xyz = np.eye(4)
sliceSpacing = abs(data[0].ImagePositionPatient[2] -
data[1].ImagePositionPatient[2])
ConstPixelSpacing = [
sliceSpacing, data[0].PixelSpacing[0], data[0].PixelSpacing[1]
]
return voxel_ndarray, ConstPixelSpacing
def main():
args = getArguments(getParser())
# prepare logger
logger = Logger.getInstance()
if args.debug: logger.setLevel(logging.DEBUG)
elif args.verbose: logger.setLevel(logging.INFO)
# load dicom slices
[series] = pydicom_series.read_files(args.input, False, True) # second to not show progress bar, third to retrieve data
#print series.sampling # Note: The first value is the mean of all differences between ImagePositionPatient-values of the DICOM slices - of course total bullshit
data_3d = series.get_pixel_array()
# check parameters
if args.dimension >= data_3d.ndim or args.dimension < 0:
raise ArgumentError('The image has only {} dimensions. The supplied target dimension {} exceeds this number.'.format(
data_3d.ndim,
args.dimension))
if not 0 == data_3d.shape[args.dimension] % args.offset:
raise ArgumentError('The number of slices {} in the target dimension {} of the image shape {} is not dividable by the supplied number of consecutive slices {}.'.format(
data_3d.shape[args.dimension],
args.dimension,
data_3d.shape,
args.offset))
# prepare empty target volume
volumes_3d = data_3d.shape[args.dimension] / args.offset
shape_4d = list(data_3d.shape)
shape_4d[args.dimension] = volumes_3d
data_4d = scipy.zeros([args.offset] + shape_4d, dtype=data_3d.dtype)
logger.debug('Separating {} slices into {} 3D volumes of thickness {}.'.format(data_3d.shape[args.dimension], volumes_3d, args.offset))
# iterate over 3D image and create sub volumes which are then added to the 4d volume
for idx in range(args.offset):
# collect the slices
for sl in range(volumes_3d):
idx_from = [slice(None), slice(None), slice(None)]
idx_from[args.dimension] = slice(idx + sl * args.offset, idx + sl * args.offset + 1)
idx_to = [slice(None), slice(None), slice(None)]
idx_to[args.dimension] = slice(sl, sl+1)
#print 'Slice {} to {}.'.format(idx_from, idx_to)
data_4d[idx][idx_to] = data_3d[idx_from]
# flip dimensions such that the newly created is the last
data_4d = scipy.swapaxes(data_4d, 0, 3)
# save resulting 4D volume
save(data_4d, args.output, False, args.force)
logger.info("Successfully terminated.")
def main():
args = getArguments(getParser())
# prepare logger
logger = Logger.getInstance()
if args.debug: logger.setLevel(logging.DEBUG)
elif args.verbose: logger.setLevel(logging.INFO)
# load input slices
[series] = pydicom_series.read_files(args.input, False, True) # second to not show progress bar, third to retrieve data
data_input = series.get_pixel_array()
if args.spacing:
print '{} {}'.format(*series.info.PixelSpacing)
return 0
logger.debug('Resulting shape is {}.'.format(data_input.shape))
# save resulting volume
save(data_input, args.output, False, args.force)
logger.info("Successfully terminated.")
def main():
args = getArguments(getParser())
# prepare logger
logger = Logger.getInstance()
if args.debug: logger.setLevel(logging.DEBUG)
elif args.verbose: logger.setLevel(logging.INFO)
# load input slices
[series] = pydicom_series.read_files(args.input, False, True) # second to not show progress bar, third to retrieve data
data_input = series.get_pixel_array()
if args.spacing:
print '{} {}'.format(*series.info.PixelSpacing)
return 0
logger.debug('Resulting shape is {}.'.format(data_input.shape))
# save resulting volume
save(data_input, args.output, False, args.force)
logger.info("Successfully terminated.")
def _load(self):
self.files = _get_files(self.file_dir, self.file_pattern)
self.stack = dicomSeries.read_files(self.files, showProgress=True, readPixelData=True)[0]
if HAS_GIAS:
self._make_scan()
