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GE ISTHMUS/Hyper Sequence #137

Merged
merged 13 commits into from
Jul 3, 2024
Merged

GE ISTHMUS/Hyper Sequence #137

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0ba6ad0
Update ge_pfile.py
agudmundson Jul 21, 2023
7dad34a
Update ge_read_pfile.py
agudmundson Jul 21, 2023
3e2e36f
Update "Dim_"
agudmundson Aug 4, 2023
01fbbbd
Hyper Echo Time for Long TE
agudmundson Aug 4, 2023
dfd39eb
Update twix_special_case.py
agudmundson Aug 4, 2023
d8220c5
Update twix_special_case.py
agudmundson Aug 4, 2023
d98db36
Merge branch 'wtclarke:master' into twix_hyper
agudmundson Aug 8, 2023
92956f2
GE ISTHMUS/Hyper Sequence
agudmundson May 22, 2024
726d0c3
Merge branch 'master' into twix_hyper
wtclarke Jun 27, 2024
fa2f60b
Update ge_hdr_fields.py
wtclarke Jun 27, 2024
7d9155a
Fix linting, line 349 still has undefined variables on.
wtclarke Jun 27, 2024
a320f50
Fix up leftover strings from twix special handling
wtclarke Jun 27, 2024
058bd0b
Merge remote-tracking branch 'origin/master' into twix_hyper
wtclarke Jul 3, 2024
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139 changes: 139 additions & 0 deletions spec2nii/GE/ge_pfile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -107,6 +107,8 @@ def _process_svs_pfile(pfile):
data, meta, dwelltime, fname_suffix = _process_slaser(pfile)
elif psd in ('jpress', 'jpress_ac', 'gaba', 'hbcd', 'probe-p-mega_rml', 'repress7'):
data, meta, dwelltime, fname_suffix = _process_gaba(pfile)
elif psd in ('hbcd'): # ATG
data, meta, dwelltime, fname_suffix = _process_hbcd(pfile) # ATG
else:
raise UnsupportedPulseSequenceError(f'Unrecognised sequence {psd}.')

Expand Down Expand Up @@ -271,6 +273,143 @@ def _process_gaba(pfile):
return [metab, water], [meta, meta_ref], dwelltime, ['', '_ref']


def _process_hbcd(pfile):
"""
Input:
Pfile Object

Output:
List of NumPy Data Arrays
List of File Name Suffixes

Details:
Hyper/ISTHMUS Sequence

The Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS)
incorporates a Short TE (35ms) PRESS, Long-TE (80ms) HERCULES, and
a water reference for each.

Data is organized within the file as follows:
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Long TE Edited : 80ms Water Suppressed HERCULES
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Long TE Reference : 80ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS
( 1) Short TE Reference : 35ms Unsupressed Water
(32) Short TE Unedited : 35ms Water Suppressed PRESS

Data is directly separated from the raw data (pfile.map.raw_data) where the data
mapper (GABA mapper) is simply used to populate in the raw data.

Author : Aaron Gudmundson, Johns Hopkins University, 2024
Contact: [email protected]
"""

# Additional Imports
import copy

# Editing Parameters
edit_cases = 4 # 4 Editing Conditions
edit_pulse_1 = 4.58 # 4.58 ppm
edit_pulse_2 = 1.90 # 1.90 ppm
edit_pulse_4 = 4.18 # 4.18 ppm
pulse_length = 0.02 # Edit Pulse 20 ms

dim_header = {'EditCondition': ['A', 'B', 'C', 'D']} # 4 Subscans
edit_pulse_val = {'A': {'PulseOffset': [edit_pulse_1, edit_pulse_2], 'PulseDuration': pulse_length},
'B': {'PulseOffset': [edit_pulse_4, edit_pulse_2], 'PulseDuration': pulse_length},
'C': {'PulseOffset': edit_pulse_1, 'PulseDuration': pulse_length},
'D': {'PulseOffset': edit_pulse_4, 'PulseDuration': pulse_length}}

# All Data (Skip 1st Transient - GE automatically has historically included a 'noise' transient)
raw_data = pfile.map.raw_data[:, :, :, :, 1:, :] # Raw Data from Mapper

# Long TE HERCULES Metabolite Data
lTE_metab = copy.deepcopy(raw_data) # Long TE Metab
lTE_mask = np.ones(lTE_metab.shape[4], dtype=bool) # Create a Mask
lTE_mask[::33] = False # Remove Water Refs
lTE_mask[: 33] = False # Remove PRESS
lTE_metab = lTE_metab[:, :, :, :, lTE_mask, :] # Isolated HERCULES

# Handle Incomplete
if lTE_mask.shape[-1] % 4 != 0: # Incomplete Acquisition
old_num_avgs = lTE_mask.shape[-1] # Old Total Averages
new_num_avgs = (lTE_mask.shape[-1] // 4) * 4 # New Total Averages
lTE_metab = lTE_metab[:, :, :, :, :new_num_avgs, :] # Remove Incomplete

notestring = f'{subseq:3d} {subseq_name:<20}' # Note Incomplete Data
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notestring = f'{notestring} - Correcting - Incomplete Averages' # Note Incomplete Data
notestring = f'{notestring} {old_num_avgs} --> {new_num_avgs}' # Note Incomplete Data
print(f'{notestring} \t Corrected**') # Note Incomplete Data

bef_shape = list(lTE_metab.shape) # Remove Averages Dim
bef_shape[4] = bef_shape[4] // 4 # Closest multiple of 4
bef_shape.append(edit_cases) # Include Subscans
lTE_metab = lTE_metab.reshape(bef_shape) # With Subscan Dim

lTE_metab_meta = _populate_metadata(pfile, water_suppressed=True) # Acquisition Information
lTE_metab_meta.set_standard_def('EchoTime', 0.080) # TE
lTE_metab_meta.set_standard_def('WaterSuppressed', True) # Water Suppression
lTE_metab_meta.set_standard_def('EditPulse', edit_pulse_val) # Header Edit Info

lTE_metab_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
lTE_metab_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info
lTE_metab_meta.set_dim_info(2, 'DIM_EDIT', hdr=dim_header) # Dimension Info

# Short TE HERCULES Metabolite Data
sTE_metab = copy.deepcopy(raw_data[:, :, :, :, 1:33, :])

sTE_metab_meta = _populate_metadata(pfile, water_suppressed=True) # Acquisition Information
sTE_metab_meta.set_standard_def('EchoTime', 0.035) # TE
sTE_metab_meta.set_standard_def('WaterSuppressed', True) # Water Suppression

sTE_metab_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
sTE_metab_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info

# Long TE Reference Water Data
lTE_water = copy.deepcopy(raw_data[:, :, :, :, 0::66, :])

lTE_water_meta = _populate_metadata(pfile, water_suppressed=False) # Acquisition Information
lTE_water_meta.set_standard_def('EchoTime', 0.080) # TE
lTE_water_meta.set_standard_def('WaterSuppressed', False) # Water Suppression

lTE_water_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
lTE_water_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info

# Short TE Reference Water Data
sTE_water = copy.deepcopy(raw_data[:, :, :, :, 33::66, :])

sTE_water_meta = _populate_metadata(pfile, water_suppressed=False) # Acquisition Information
sTE_water_meta.set_standard_def('EchoTime', 0.035) # TE
sTE_water_meta.set_standard_def('WaterSuppressed', False) # Water Suppression

sTE_water_meta.set_dim_info(0, 'DIM_DYN') # Dimension Info
sTE_water_meta.set_dim_info(1, 'DIM_COIL') # Dimension Info

# Dwell Time
dwelltime = 1 / pfile.hdr.rhr_spectral_width

data = [lTE_metab, sTE_metab, lTE_water, sTE_water] # ISTHMUS Data
meta = [lTE_metab_meta, sTE_metab_meta, lTE_water_meta, sTE_water_meta] # ISTHMUS Header
ref_names = ['_edited', '_short_te', '_ref_edited', '_ref_short_te'] # ISTHMUS Naming

print('Returning ISTHMUS Data:')
for ii in range(len(data)):
print(' {:02d} {:<14} '.format(ii, ref_names[ii]), data[ii].shape)
print(' ')

return data, meta, dwelltime, ref_names


def _process_mrsi_pfile(pfile):
"""Handle MRSI data

Expand Down
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