def setUp(self):
# TODO: remake ge_dcm_screenshot with json
self.ds = scidata.parse(os.path.join(DATADIR,
'ge_dcm_sc_screenshot.tgz'),
load_data=True,
filetype='dicom',
ignore_json=True)
def test_parse(self):
"""
Parse one dicom as header.
NIMSDicom parses a single dicom, using nimsdicom.MetaExtractor, upon initialization.
"""
# test 1 - keeps private tags
# this test is rather indirect, nimsdicom uses the MetaExtractor
# to set the dataset._hdr, testing it this way, allows re-using one of the test files
ds = scidata.parse(os.path.join(DATADIR, 'ge_dcm_mr_localizer.tgz'))
ok_(ds._hdr.get('PrivateCreator_0X9_0X0')) # try getting the first PrivateCreator, tag (0x0009,0x0000)
def test_parse(self):
"""
Parse one dicom as header.
NIMSDicom parses a single dicom, using nimsdicom.MetaExtractor, upon initialization.
"""
# test 1 - keeps private tags
# this test is rather indirect, nimsdicom uses the MetaExtractor
# to set the dataset._hdr, testing it this way, allows re-using one of the test files
ds = scidata.parse(os.path.join(DATADIR, 'ge_dcm_mr_localizer.tgz'))
ok_(ds._hdr.get('PrivateCreator_0X9_0X0')
) # try getting the first PrivateCreator, tag (0x0009,0x0000)
def setUp(self):
testdata = os.path.join(DATADIR, 'ge_dcm_mr_localizer.tgz')
self.ds = scidata.parse(testdata, load_data=True)
def setUp(self):
# TODO: remake ge_dcm_screenshot with json
self.ds = scidata.parse(os.path.join(DATADIR, 'ge_dcm_sc_screenshot.tgz'), load_data=True, filetype='dicom', ignore_json=True)
def process(self):
log.info('reconstructing and concatenating')
outfiles = []
first_tr = None
with tempfile.TemporaryDirectory(dir=None) as temp_dirpath:
for f in self.inputs:
fpath = os.path.abspath(f)
dcm_ds = scidata.parse(fpath, filetype='dicom', load_data=True, ignore_json=True)
if not first_tr:
first_tr = dcm_ds.tr
# save info to name this nifti
label = '%s_%s' % (dcm_ds.exam_no, dcm_ds.series_no)
# GLU: label = '%s' % (dcm_ds.protocol_name)
intermediate = os.path.join(temp_dirpath, '_%s' % label)
# save info to name the final output
if not self.outbase:
self.outbase = os.path.join(label + '_multicoil.nii.gz')
result = scidata.write(dcm_ds, dcm_ds.data, intermediate, filetype='nifti', voxel_order=self.voxel_order)
log.debug('reconstructed nifti: %s' % result)
# maintain a list of intermediate files
outfiles += result
first_nii_header = None
first_qto_xyz = None # to be able to check if any is saved at all.
seq = []
# create a sequence from the intermediate files
# resulting sequence items should have consistent dimensions
log.debug('combinging niftis: %s' % str(outfiles))
for f in outfiles:
nii = dcmstack.dcmmeta.NiftiWrapper(nibabel.load(f), make_empty=True)
# store the header from the first outfile
if first_nii_header is None:
log.debug('storing first input nifti header')
first_nii_header = nii.nii_img.get_header()
if first_qto_xyz is None: # is array set?
log.debug('storing first input affine')
first_qto_xyz = nii.nii_img.get_affine()
# build up the sequence of nifti wrappers
if len(nii.nii_img.get_shape()) == 4:
seq += [nii_wrp for nii_wrp in nii.split()]
else:
seq += [nii]
# combine the sequence of nifti wrappers, raises error if shapes not consistent
nii_merge = dcmstack.dcmmeta.NiftiWrapper.from_sequence(seq)
nii_merge.nii_img.update_header() # update the underlying nifti header
nii_header = nii_merge.nii_img.get_header() # reference to underlying nifti header
# adjust the new header
nii_header['descrip'] = first_nii_header['descrip']
data = nii_merge.nii_img.get_data()
if np.iscomplexobj(data):
clip_vals = np.percentile(np.abs(data), (10.0, 99.5))
else:
clip_vals = np.percentile(data, (10.0, 99.5))
nii_header.structarr['cal_min'] = clip_vals[0]
nii_header.structarr['cal_max'] = clip_vals[1]
nii_header['pixdim'][4] = first_tr
if os.path.exists(self.outbase):
raise ProcessorError('output file %s already exists. not overwriting. bailing.', log_level=logging.ERROR)
else:
nii_merge.to_filename(self.outbase)
if os.path.exists(self.outbase):
log.info('generated %s' % self.outbase)
else:
raise ProcessorError('output file %s does not exist?' % self.outbase, log_level=logging.ERROR)
return [self.outbase]
def setUp(self):
testdata = os.path.join(DATADIR, 'ge_dcm_mr_localizer.tgz')
self.ds = scidata.parse(testdata, load_data=True)