git clone https://github.com/wtclarke/mrs_nifti_standard.git

nifti_mrs_file = 'svs_preprocessed.nii.gz';
img = nib.load(nifti_mrs_file)

data = img.get_fdata(dtype=np.complex64)
print(f'Data shape = {data.shape}')

Data shape = (1, 1, 1, 4096)

fig,axes = plt.subplots(1,2,figsize=(15,4))
axes[0].plot(np.abs(data[0,0,0,:]),color='k')
axes[1].plot(np.real(data[0,0,0,:]),color='r')
plt.savefig('plots/data.png')

header = img.header
print(f'intent_name: {header.get_intent()[2]}')
print(f'Position information: \n {header.get_best_affine()}\n')

dwelltime = header['pixdim'][4]
print(f'Dwelltime: {dwelltime} s\n')

print(header)

intent_name: mrs_v0_2
Position information: 
[[ 20.          -0.          -0.         -32.90067836]
[ -0.         -20.          -0.          10.6633755 ]
[  0.           0.         -20.          21.35589036]
[  0.           0.           0.           1.        ]]

Dwelltime: 8.33e-05 s

<class 'nibabel.nifti2.Nifti2Header'> object, endian='<'
sizeof_hdr      : 540
magic           : b'n+2'
eol_check       : [13 10 26 10]
datatype        : complex64
bitpix          : 64
dim             : [   4    1    1    1 4096    1    1    1]
intent_p1       : 0.0
intent_p2       : 0.0
intent_p3       : 0.0
pixdim          : [1.00e+00 2.00e+01 2.00e+01 2.00e+01 8.33e-05 1.00e+00 1.00e+00 1.00e+00]
vox_offset      : 0
scl_slope       : nan
scl_inter       : nan
cal_max         : 0.0
cal_min         : 0.0
slice_duration  : 0.0
toffset         : 0.0
slice_start     : 0
slice_end       : 0
descrip         : b''
aux_file        : b''
qform_code      : aligned
sform_code      : aligned
quatern_b       : 1.0
quatern_c       : 0.0
quatern_d       : 0.0
qoffset_x       : -32.90067836
qoffset_y       : 10.6633755
qoffset_z       : 21.35589036
srow_x          : [ 20.          -0.          -0.         -32.90067836]
srow_y          : [ -0.        -20.         -0.         10.6633755]
srow_z          : [  0.           0.         -20.          21.35589036]
slice_code      : unknown
xyzt_units      : 0
intent_code     : none
intent_name     : b'mrs_v0_2'
dim_info        : 0
unused_str      : b''

hdr_ext_codes = img.header.extensions.get_codes()
mrs_hdr_ext = json.loads(img.header.extensions[hdr_ext_codes.index(44)].get_content())
mrs_hdr_ext

{'SpectrometerFrequency': [297.219948],
'ResonantNucleus': ['1H'],
'EchoTime': 0.011,
'RepetitionTime': 5.0,
'InversionTime': None,
'MixingTime': 0.032,
'ConversionMethod': 'Manual',
'ConversionTime': '2020-12-16T17:14:47.920',
'OriginalFile': ['meas_MID310_STEAM_metab_FID115673.dat']}

spectrometer_frequency = mrs_hdr_ext['SpectrometerFrequency'][0]
bandwidth = 1/dwelltime
frequency_axis = np.linspace(bandwidth/2, -bandwidth/2, data.shape[3])
ppm_axis = 4.65+frequency_axis/spectrometer_frequency

spectrum = np.fft.fftshift(np.fft.fft(data[0,0,0,:]))

fig,(ax1,ax2) = plt.subplots(2,1,figsize=(15,7))
ax1.plot(frequency_axis,np.real(spectrum))
ax2.plot(ppm_axis,np.real(spectrum))

ax1.invert_xaxis()
ax2.invert_xaxis()

ax1.set_xlabel('$|\omega|-|\omega_{ref}|$ (Hz)')
ax2.set_xlabel('$\delta$ (ppm)')

plt.savefig('plots/spectra.png')

nifti_mrs_file_2 = 'svs_suppressed.nii.gz';
img2 = nib.load(nifti_mrs_file_2)

print(f'Data shape: {img2.get_fdata(dtype=np.complex64).shape}')

Data shape: (1, 1, 1, 4096, 32, 64)

hdr_ext_codes = img2.header.extensions.get_codes()
mrs_hdr_ext2 = json.loads(img2.header.extensions[hdr_ext_codes.index(44)].get_content())
mrs_hdr_ext2

{'dim_5': 'DIM_COIL',
'dim_6': 'DIM_DYN',
'dim_6_use': 'Signal repetitions',
'SpectrometerFrequency': [297.219948],
'ResonantNucleus': ['1H'],
'EchoTime': 0.011,
'RepetitionTime': 5.0,
'InversionTime': None,
'MixingTime': 0.032,
'ConversionMethod': 'Manual',
'ConversionTime': '2020-12-16T17:14:47.920',
'OriginalFile': ['meas_MID310_STEAM_metab_FID115673.dat'],
'siemens_sequence_info': {'Description': 'Paths to sequence and reconstruction code binaries for sequence identification.',
'sequence': '%CustomerSeq%\\uzay_steam_gui',
'recon': '%CustomerIceProgs%\\uzayIcePrgSpecOnline'}}