def parse_one(self):
"""
Composer function, parses all metadata that can be parsed from a single dicom.
Called by NIMSDicom init, if dicom manufacturer is Siemens.
"""
mr.parse_standard_mr_tags(self)
self.psd_name = self.getelem(
self._hdr, 'CsaSeries.MrPhoenixProtocol.tSequenceFileName', str,
'').lower().replace('%', '', 1)
self.psd_iname = self.getelem(self._hdr, 'SeriesDescription')
self.fov_x = self.getelem(
self._hdr,
'CsaSeries.MrPhoenixProtocol.sSliceArray.asSlice[0].dPhaseFOV',
float) # XXX fov-x = PhaseFOV?
self.fov_y = self.getelem(
self._hdr,
'CsaSeries.MrPhoenixProtocol.sSliceArray.asSlice[0].dReadoutFOV',
float) # XXX fov-y = ReadoutFOV?
self.receive_coil_name = self.getelem(self._hdr, 'CsaImage.ImaCoilString')
slice_duration = self.getelem(self._hdr,
'CsaImage.SliceMeasurementDuration', float,
0.)
self.slice_duration = slice_duration / 1e6 if slice_duration else None
self.prescribed_duration = self.getelem(
self._hdr, 'CsaSeries.MrPhoenixProtocol.lScanTimeSec') # FIXME
self.duration = self.getelem(
self._hdr, 'CsaSeries.MrPhoenixProtocol.lTotalScanTimeSec'
) # FIXME: not guaranteed
self.acq_no = None # siemens acq # indicates the brain volume instance. varies within one scan.
# this is not an ideal solution, as it assumes that EPI timeserise are always stored in mosaic
# for mosaics, lReps = prescribed timepoints. non-mosaics and non-timeseries will not have this tag
lRep = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.lRepetitions',
int)
self.num_timepoints = (lRep + 1) if lRep else None
self.dwi_dirs = self.getelem(
self._hdr, 'CsaSeries.MrPhoenixProtocol.sDiffusion.lDiffDirections',
int, None)
if (self.dwi_dirs or 0) > 1:
self.is_dwi = True
self.num_timepoints = 1
# some siemens MR dicoms are not reconstructable
if 'CSAPARALLEL' in self.image_type:
self.is_non_image = True
if 'POSDISP' in self.image_type:
self.is_non_image = True
if self.image_type == SIEMENS_TYPE_DIS2D:
# had 2 image orientations, and other metdata that varied between dicoms, and is not a localizer. AFNI cannot reconstsruct.
# this is a specific hack fix. A more general fix is to check each dicom to see if the orientation matches the first dicom
# but checking EVERY dicom isn't very ideal solution (some datasets might have an ENORMOUS number of dicoms)
self.is_non_image = True
infer_psd_type(self)
mr.adjust_fov_acqmat(self)
mr.infer_scan_type(self)
def parse_one(self):
"""
Composer function, parses all metadata that can be parsed from a single dicom.
Called by NIMSDicom init, if dicom manufacturer is Siemens.
"""
mr.parse_standard_mr_tags(self)
self.psd_name = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.tSequenceFileName', str, '').lower().replace('%', '', 1)
self.psd_iname = self.getelem(self._hdr, 'SeriesDescription')
self.fov_x = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.sSliceArray.asSlice[0].dPhaseFOV', float) # XXX fov-x = PhaseFOV?
self.fov_y = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.sSliceArray.asSlice[0].dReadoutFOV', float) # XXX fov-y = ReadoutFOV?
self.receive_coil_name = self.getelem(self._hdr, 'CsaImage.ImaCoilString')
slice_duration = self.getelem(self._hdr, 'CsaImage.SliceMeasurementDuration', float, 0.)
self.slice_duration = slice_duration / 1e6 if slice_duration else None
self.prescribed_duration = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.lScanTimeSec') # FIXME
self.duration = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.lTotalScanTimeSec') # FIXME: not guaranteed
self.acq_no = None # siemens acq # indicates the brain volume instance. varies within one scan.
# this is not an ideal solution, as it assumes that EPI timeserise are always stored in mosaic
# for mosaics, lReps = prescribed timepoints. non-mosaics and non-timeseries will not have this tag
lRep = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.lRepetitions', int)
self.num_timepoints = (lRep + 1) if lRep else None
self.dwi_dirs = self.getelem(self._hdr, 'CsaSeries.MrPhoenixProtocol.sDiffusion.lDiffDirections', int, None)
if (self.dwi_dirs or 0) > 1:
self.is_dwi = True
self.num_timepoints = 1
# some siemens MR dicoms are not reconstructable
if 'CSAPARALLEL' in self.image_type:
self.is_non_image = True
if 'POSDISP' in self.image_type:
self.is_non_image = True
if self.image_type == SIEMENS_TYPE_DIS2D:
# had 2 image orientations, and other metdata that varied between dicoms, and is not a localizer. AFNI cannot reconstsruct.
# this is a specific hack fix. A more general fix is to check each dicom to see if the orientation matches the first dicom
# but checking EVERY dicom isn't very ideal solution (some datasets might have an ENORMOUS number of dicoms)
self.is_non_image = True
infer_psd_type(self)
mr.adjust_fov_acqmat(self)
mr.infer_scan_type(self)
def parse_one(self):
"""
Composer function, parses all metadata that can be parsed from a single dicom.
Called by NIMSData init, if dicom manufacturer is GE Medical Sytems.
"""
mr.parse_standard_mr_tags(self)
self.psd_name = self.getelem(self._hdr, 'PulseSequenceName', str,
'').lower()
self.psd_iname = self.getelem(self._hdr, 'InternalPulseSequenceName')
self.fov_x, self.fov_y = 2 * [
self.getelem(self._hdr, 'ReconstructionDiameter', float)
]
self.receive_coil_name = self.getelem(self._hdr, 'ReceiveCoilName')
self.mt_offset_hz = self.getelem(self._hdr, 'OffsetFrequency', float)
effective_echo_spacing = self.getelem(self._hdr, 'EffectiveEchoSpacing',
float)
self.effective_echo_spacing = effective_echo_spacing / 1e6 if effective_echo_spacing else None
asset_r = self.getelem(self._hdr, 'AssetRFactors', None, [None, None])
if isinstance(
asset_r, unicode
) and '\\' in asset_r: # GE Signa HDxt stores asset as string '1\1'
asset_r = map(
int, asset_r.split('\\')) # reformat to [1, 1] for consistency
elif isinstance(asset_r, float): # asset_r can be single item float
asset_r = [None, None]
self.phase_encode_undersample, self.slice_encode_undersample = asset_r
# some very old Ge systems will output dicoms that don't define Locations in Acquition, or define it in a way
# that is weird. It may incorrectly label the value type as OB, but not be able to translate the value, resulting
# in the MetaExtractor excluding it from the it's output metadata.
self.num_slices = self.getelem(self._hdr, 'LocationsInAcquisition', int)
self.total_num_slices = self.getelem(self._hdr, 'ImagesInAcquisition', int)
self.num_timepoints = self.getelem(self._hdr, 'NumberOfTemporalPositions',
int)
# slice check could end up wrong, if both total_num_slices and num_slices are None
# could force num_slices and total_num_slices into different ORs, to prevent matching if both are None
# thus only when they are both defined, AND not equal, can this test pass
if (self.total_num_slices or 1) == (self.num_slices or 0):
self.total_num_slices = (self.num_slices or 1) * (self.num_timepoints
or 1)
log.debug('adjusted total_num_slices from %3d to %3d' %
(self.num_slices,
self.total_num_slices)) # num_slices == 'old' total_num
# some localizer don't have header field to indicate the number of slices
# per acquisition. If the total_number of slices is set, and the num_timepoints is 1
# then the number of slices should be equal to total number of slices
if not self.num_slices and (self.num_timepoints or 1) == 1:
self.num_slices = self.total_num_slices
prescribed_duration = (self.tr or 0) * (self.num_timepoints or 0) * (
self.num_averages or 1) # FIXME: only works for fMRI, not anatomical
if prescribed_duration != 0:
self.prescribed_duration = prescribed_duration
self.duration = prescribed_duration
else:
self.prescribed_duration = None
self.duration = None
dwi_dirs = self.getelem(self._hdr,
'UserData24{#DTIDiffusionDir.,Release10.0&Above}',
float)
self.dwi_dirs = int(dwi_dirs) if dwi_dirs else None
if self.image_type == GEMS_TYPE_ORIG and (self.dwi_dirs or 0) >= 6:
self.is_dwi = True
self.num_timepoints = 1
if self.image_type == GEMS_TYPE_DERIVED_RFMT:
self.is_non_image = True
infer_psd_type(self)
mr.adjust_fov_acqmat(self)
mr.infer_scan_type(self)
def parse_one(self):
"""
Composer function, parses all metadata that can be parsed from a single dicom.
Called by NIMSData init, if dicom manufacturer is GE Medical Sytems.
"""
mr.parse_standard_mr_tags(self)
self.psd_name = self.getelem(self._hdr, 'PulseSequenceName', str, '').lower()
self.psd_iname = self.getelem(self._hdr, 'InternalPulseSequenceName')
self.fov_x, self.fov_y = 2 * [self.getelem(self._hdr, 'ReconstructionDiameter', float)]
self.receive_coil_name = self.getelem(self._hdr, 'ReceiveCoilName')
self.mt_offset_hz = self.getelem(self._hdr, 'OffsetFrequency', float)
effective_echo_spacing = self.getelem(self._hdr, 'EffectiveEchoSpacing', float)
self.effective_echo_spacing = effective_echo_spacing / 1e6 if effective_echo_spacing else None
asset_r = self.getelem(self._hdr, 'AssetRFactors', None, [None, None])
if isinstance(asset_r, unicode) and '\\' in asset_r: # GE Signa HDxt stores asset as string '1\1'
asset_r = map(int, asset_r.split('\\')) # reformat to [1, 1] for consistency
elif isinstance(asset_r, float): # asset_r can be single item float
asset_r = [None, None]
self.phase_encode_undersample, self.slice_encode_undersample = asset_r
# some very old Ge systems will output dicoms that don't define Locations in Acquition, or define it in a way
# that is weird. It may incorrectly label the value type as OB, but not be able to translate the value, resulting
# in the MetaExtractor excluding it from the it's output metadata.
self.num_slices = self.getelem(self._hdr, 'LocationsInAcquisition', int)
self.total_num_slices = self.getelem(self._hdr, 'ImagesInAcquisition', int)
self.num_timepoints = self.getelem(self._hdr, 'NumberOfTemporalPositions', int)
# slice check could end up wrong, if both total_num_slices and num_slices are None
# could force num_slices and total_num_slices into different ORs, to prevent matching if both are None
# thus only when they are both defined, AND not equal, can this test pass
if (self.total_num_slices or 1) == (self.num_slices or 0):
self.total_num_slices = (self.num_slices or 1) * (self.num_timepoints or 1)
log.debug('adjusted total_num_slices from %3d to %3d' % (self.num_slices, self.total_num_slices)) # num_slices == 'old' total_num
# some localizer don't have header field to indicate the number of slices
# per acquisition. If the total_number of slices is set, and the num_timepoints is 1
# then the number of slices should be equal to total number of slices
if not self.num_slices and (self.num_timepoints or 1) == 1:
self.num_slices = self.total_num_slices
prescribed_duration = (self.tr or 0) * (self.num_timepoints or 0) * (self.num_averages or 1) # FIXME: only works for fMRI, not anatomical
if prescribed_duration != 0:
self.prescribed_duration = prescribed_duration
self.duration = prescribed_duration
else:
self.prescribed_duration = None
self.duration = None
dwi_dirs = self.getelem(self._hdr, 'UserData24{#DTIDiffusionDir.,Release10.0&Above}', float)
self.dwi_dirs = int(dwi_dirs) if dwi_dirs else None
if self.image_type == GEMS_TYPE_ORIG and (self.dwi_dirs or 0) >= 6:
self.is_dwi = True
self.num_timepoints = 1
if self.image_type == GEMS_TYPE_DERIVED_RFMT:
self.is_non_image = True
infer_psd_type(self)
mr.adjust_fov_acqmat(self)
mr.infer_scan_type(self)
