def mmrinit():
# get the constants for the mMR
Cnt = resources.get_mmr_constants()
# transaxial look up tables
txLUT = transaxial_lut(Cnt)
Cnt['Naw'] = txLUT['Naw']
# axial look up tables
axLUT = axial_lut(Cnt)
return Cnt, txLUT, axLUT
def check_constants():
'''get the constants for the mMR from the resources file before
getting the path to the local resources.py (on Linux machines it is in ~/.niftypet)'''
path_resources = path_niftypet_local()
# import resource
sys.path.append(path_resources)
try:
import resources
except ImportError as ie:
print '----------------------------'
print 'e> Import Error: NiftyPET' 's resources file <resources.py> could not be imported. It should be in ' '~/.niftypet/resources.py' ' but likely it does not exists.'
print '----------------------------'
raise ImportError('Could not find resources.py')
#===========================
Cnt = resources.get_mmr_constants()
sct_compile = chck_sct_h(Cnt)
def_compile = chck_vox_h(Cnt)
print '----------------------------'
print 'changed sct.h:', sct_compile
print 'changed def.h:', def_compile
print '----------------------------'
if sct_compile or def_compile:
print 'i> NiftyPET constants were changed: needs CUDA compilation.'
def fwhm2sig(fwhm):
Cnt = resources.get_mmr_constants()
return (fwhm / Cnt['SZ_VOXY']) / (2 * (2 * np.log(2))**.5)
def align_mumap(
datain,
scanner_params={},
outpath='',
use_stored=False,
hst=[],
t0=0, t1=0,
itr=2,
faff='',
fpet='',
fcomment='',
store=False,
store_npy=False,
petopt='ac',
musrc='ute', # another option is pct for mu-map source
ute_name='UTE2',
del_auxilary=True,
verbose=True,
):
'''
Align the a pCT or MR-derived mu-map to a PET image reconstructed to chosen
specifications (e.g., with/without attenuation and scatter corrections)
use_sotred only works if hst or t0/t1 given but not when faff.
'''
#> output folder
if outpath=='':
opth = os.path.join( datain['corepath'], 'mumap-obj' )
else:
opth = os.path.join( outpath, 'mumap-obj' )
#> create the folder, if not existent
nimpa.create_dir(opth)
#> get the timing of PET if affine not given
if faff!='' and 't0' in hst:
t0 = hst['t0']
t1 = hst['t1']
#> file name for the output mu-map
fnm = 'mumap-' + musrc.upper()
#> output dictionary
mu_dct = {}
#---------------------------------------------------------------------------
#> used stored if requested
if use_stored and affine!='':
fmu_stored = fnm + '-aligned-to_t'\
+ str(hst['t0'])+'-'+str(hst['t1'])+'_'+petopt.upper()\
+ fcomment
fmupath = os.path.join(opth, fmu_stored)
if os.path.isfile( fmupath ):
mudct_stored = nimpa.getnii(fmupath, output='all')
#> create output dictionary
mu_dct['im'] = mudct_stored['im']
mu_dct['affine'] = mudct_stored['affine']
#mu_dct['faff'] = faff
return mu_dct
#---------------------------------------------------------------------------
#> three ways of passing scanner constants <Cnt> are here decoded
if 'Cnt' in scanner_params:
Cnt = scanner_params['Cnt']
elif 'SO_IMZ' in scanner_params:
Cnt = scanner_params
else:
Cnt = rs.get_mmr_constants()
Cnt = scanner_params['Cnt']
#> if affine not provided histogram the LM data for recon and registration
if not os.path.isfile(faff):
from niftypet.nipet.prj import mmrrec
#-histogram the list data if needed
if not hst:
from niftypet.nipet import mmrhist
if 'txLUT' in scanner_params:
hst = mmrhist(datain, scanner_params, t0=t0, t1=t1)
else:
raise ValueError(
'e> full scanner parameters not provided\
but required for histogramming.')
#=========================================================
#-get hardware mu-map
if 'hmumap' in datain and os.path.isfile(datain['hmumap']):
muh, _, _ = np.load(datain['hmumap'], allow_pickle=True)
if verbose: print 'i> loaded hardware mu-map from file:', datain['hmumap']
elif outpath!='':
hmupath = os.path.join( os.path.join(outpath,'mumap-hdw'), 'hmumap.npy')
if os.path.isfile( hmupath ):
muh, _, _ = np.load(hmupath, allow_pickle=True)
datain['hmumap'] = hmupath
else:
raise IOError('Invalid path to the hardware mu-map')
else:
print 'e> obtain the hardware mu-map first.'
raise IOError('Could not find the hardware mu-map. Have you run the routine for hardware mu-map?')
#=========================================================
#-check if T1w image is available
if not 'MRT1W#' in datain and not 'T1nii' in datain and not 'T1bc' in datain \
and not 'T1N4' in datain:
print 'e> no MR T1w images required for co-registration!'
raise IOError('T1w image could not be obtained')
#=========================================================
#-if the affine is not given,
#-it will be generated by reconstructing PET image, with some or no corrections
if not os.path.isfile(faff):
# first recon pet to get the T1 aligned to it
if petopt=='qnt':
# ---------------------------------------------
# OPTION 1 (quantitative recon with all corrections using MR-based mu-map)
# get UTE object mu-map (may not be in register with the PET data)
mudic = obj_mumap(
datain,
Cnt,
del_auxilary=del_auxilary)
muo = mudic['im']
# reconstruct PET image with UTE mu-map to which co-register T1w
recout = mmrrec.osemone(
datain, [muh, muo],
hst, scanner_params,
recmod=3, itr=itr, fwhm=0.,
fcomment=fcomment+'_QNT-UTE',
outpath=os.path.join(outpath, 'PET', 'positioning'),
store_img=True)
elif petopt=='nac':
# ---------------------------------------------
# OPTION 2 (recon without any corrections for scatter and attenuation)
# reconstruct PET image with UTE mu-map to which co-register T1w
muo = np.zeros(muh.shape, dtype=muh.dtype)
recout = mmrrec.osemone(
datain, [muh, muo],
hst, scanner_params,
recmod=1, itr=itr, fwhm=0.,
fcomment=fcomment+'_NAC',
outpath=os.path.join(outpath,'PET', 'positioning'),
store_img=True)
elif petopt=='ac':
# ---------------------------------------------
# OPTION 3 (recon with attenuation correction only but no scatter)
# reconstruct PET image with UTE mu-map to which co-register T1w
mudic = obj_mumap(
datain,
Cnt,
del_auxilary=del_auxilary)
muo = mudic['im']
recout = mmrrec.osemone(
datain, [muh, muo],
hst, scanner_params,
recmod=1, itr=itr, fwhm=0.,
fcomment=fcomment+'_AC-UTE',
outpath=os.path.join(outpath,'PET', 'positioning'),
store_img=True)
fpet = recout.fpet
mu_dct['fpet'] = fpet
#------------------------------
if musrc=='ute' and ute_name in datain and os.path.exists(datain[ute_name]):
# change to NIfTI if the UTE sequence is in DICOM files (folder)
if os.path.isdir(datain[ute_name]):
fnew = os.path.basename(datain[ute_name])
call( [ Cnt['DCM2NIIX'], '-f', fnew, datain[ute_name] ] )
fute = glob.glob(os.path.join(datain[ute_name], fnew+'*nii*'))[0]
elif os.path.isfile(datain[ute_name]):
fute = datain[ute_name]
# get the affine transformation
try:
regdct = nimpa.coreg_spm(
fpet,
fute,
outpath=os.path.join(outpath,'PET', 'positioning')
)
except:
regdct = nimpa.affine_niftyreg(
fpet,
fute,
outpath=os.path.join(outpath,'PET', 'positioning'),
#fcomment=fcomment,
executable = Cnt['REGPATH'],
omp = multiprocessing.cpu_count()/2,
rigOnly = True,
affDirect = False,
maxit=5,
speed=True,
pi=50, pv=50,
smof=0, smor=0,
rmsk=True,
fmsk=True,
rfwhm=15., #millilitres
rthrsh=0.05,
ffwhm = 15., #millilitres
fthrsh=0.05,
verbose=verbose
)
faff_mrpet = regdct['faff']
elif musrc=='pct':
ft1w = nimpa.pick_t1w(datain)
try:
regdct = nimpa.coreg_spm(
fpet,
ft1w,
outpath=os.path.join(outpath,'PET', 'positioning')
)
except:
regdct = nimpa.affine_niftyreg(
fpet,
ft1w,
outpath=os.path.join(outpath,'PET', 'positioning'),
executable = Cnt['REGPATH'],
omp = multiprocessing.cpu_count()/2,
rigOnly = True,
affDirect = False,
maxit=5,
speed=True,
pi=50, pv=50,
smof=0, smor=0,
rmsk=True,
fmsk=True,
rfwhm=15., #millilitres
rthrsh=0.05,
ffwhm = 15., #millilitres
fthrsh=0.05,
verbose=verbose
)
faff_mrpet = regdct['faff']
else:
raise IOError('Floating MR image not provided or is invalid.')
else:
faff_mrpet = faff
regdct = {}
if not os.path.isfile(fpet):
raise IOError('e> the reference PET should be supplied with the affine.')
#> output file name for the aligned mu-maps
if musrc=='pct':
freg = os.path.join(opth, 'pCT-res-tmp'+fcomment+'.nii.gz')
fflo = datain['pCT']
elif musrc=='ute':
freg = os.path.join(opth, 'UTE-res-tmp'+fcomment+'.nii.gz')
if 'UTE' not in datain:
fnii = 'converted-from-DICOM_'
tstmp = nimpa.time_stamp(simple_ascii=True)
# convert the DICOM mu-map images to nii
if 'mumapDCM' not in datain:
raise IOError('DICOM with the UTE mu-map are not given.')
call( [ Cnt['DCM2NIIX'], '-f', fnii+tstmp, '-o', opth, datain['mumapDCM'] ] )
#files for the T1w, pick one:
fflo = glob.glob( os.path.join(opth, '*'+fnii+tstmp+'*.nii*') )[0]
else:
if os.path.isfile(datain['UTE']):
fflo = datain['UTE']
else:
raise IOError('The provided NIfTI UTE path is not valid.')
#> call the resampling routine to get the pCT/UTE in place
if 'matlab_eng' in regdct:
nimpa.resample_spm(
fpet,
fflo,
faff_mrpet,
matlab_eng=regdct['matlab_eng'],
fimout=freg,
del_ref_uncmpr=True,
del_flo_uncmpr=True,
del_out_uncmpr=True
)
else:
nimpa.resample_niftyreg(
fpet,
fflo,
faff_mrpet,
fimout = freg,
executable = Cnt['RESPATH'],
verbose = True)
#-get the NIfTI of registered image
nim = nib.load(freg)
A = nim.affine
imreg = np.float32( nim.get_data() )
imreg = imreg[:,::-1,::-1]
imreg = np.transpose(imreg, (2, 1, 0))
#-convert to mu-values; sort out the file name too.
if musrc=='pct':
mu = hu2mu(imreg)
elif musrc=='ute':
mu = np.float32(imreg)/1e4
#-remove the converted file from DICOMs
os.remove(fflo)
else:
raise NameError('Confused o_O.')
# get rid of negatives
mu[mu<0] = 0
# return image dictionary with the image itself and other parameters
mu_dct['im'] = mu
mu_dct['affine'] = A
mu_dct['faff'] = faff
if store or store_npy:
nimpa.create_dir(opth)
if faff=='':
fname = fnm + '-aligned-to_t'\
+ str(hst['t0'])+'-'+str(hst['t1'])+'_'+petopt.upper()\
+ fcomment
else:
fname = fnm + '-aligned-to-given-affine' + fcomment
if store_npy:
#> Numpy
if store_to_npy:
fnp = os.path.join(opth, fname + '.npy')
np.save(fnp, (mu, A, fnp))
if store:
#> NIfTI
fmu = os.path.join(opth, fname + '.nii.gz')
nimpa.array2nii(mu[::-1,::-1,:], A, fmu)
mu_dct['fim'] = fmu
if del_auxilary:
os.remove(freg)
if not os.path.isfile(faff):
os.remove(fute)
return mu_dct
def obj_mumap(
datain,
params={},
outpath='',
comment='',
store=False,
store_npy=False,
gantry_offset=True,
del_auxilary=True,
):
'''Get the object mu-map from DICOM images'''
# three ways of passing scanner constants <Cnt> are here decoded
if 'Cnt' in params:
Cnt = params['Cnt']
elif 'SO_IMZ' in params:
Cnt = params
else:
Cnt = rs.get_mmr_constants()
# output folder
if outpath=='':
fmudir = os.path.join( datain['corepath'], 'mumap-obj' )
else:
fmudir = os.path.join( outpath, 'mumap-obj' )
nimpa.create_dir(fmudir)
# ref file name
fmuref = os.path.join(fmudir, 'muref.nii.gz')
# ref affine
B = image_affine(datain, Cnt, gantry_offset=gantry_offset)
# ref image (blank)
im = np.zeros((Cnt['SO_IMZ'], Cnt['SO_IMY'], Cnt['SO_IMX']), dtype=np.float32)
# store ref image
nimpa.array2nii(im, B, fmuref)
# check if the object dicom files for MR-based mu-map exists
if not 'mumapDCM' in datain or not os.path.isdir(datain['mumapDCM']):
print 'e> DICOM forlder for the mu-map does not exist.'
return None
fnii = 'converted-from-object-DICOM_'
tstmp = nimpa.time_stamp(simple_ascii=True)
# find residual(s) from previous runs and delete them
resdcm = glob.glob( os.path.join(fmudir, '*'+fnii+'*.nii*') )
for d in resdcm:
os.remove(d)
# convert the DICOM mu-map images to nii
call( [ Cnt['DCM2NIIX'], '-f', fnii+tstmp, '-o', fmudir, datain['mumapDCM'] ] )
#files for the T1w, pick one:
fmunii = glob.glob( os.path.join(fmudir, '*'+fnii+tstmp+'*.nii*') )[0]
# fmunii = glob.glob( os.path.join(datain['mumapDCM'], '*converted*.nii*') )
# fmunii = fmunii[0]
# the converted nii image resample to the reference size
fmu = os.path.join(fmudir, comment+'mumap_tmp.nii.gz')
if os.path.isfile( Cnt['RESPATH'] ):
cmd = [ Cnt['RESPATH'],
'-ref', fmuref,
'-flo', fmunii,
'-res', fmu,
'-pad', '0']
if not Cnt['VERBOSE']: cmd.append('-voff')
call(cmd)
else:
print 'e> path to resampling executable is incorrect!'
sys.exit()
nim = nib.load(fmu)
# get the affine transform
A = nim.get_sform()
mu = nim.get_data()
mu = np.transpose(mu[:,::-1,::-1], (2, 1, 0))
# convert to mu-values
mu = np.float32(mu)/1e4
mu[mu<0] = 0
#> return image dictionary with the image itself and some other stats
mu_dct = { 'im':mu,
'affine':A}
if not del_auxilary: mu_dct['fmuref'] = fmuref
# store the mu-map if requested
if store_npy:
# to numpy array
fnp = os.path.join(fmudir, 'mumap-from-DICOM.npy' )
np.save(fnp, (mu, A))
if store:
# with this file name
fmumap = os.path.join(fmudir, 'mumap-from-DICOM_no-alignment'+comment+'.nii.gz')
nimpa.array2nii(mu[::-1,::-1,:], A, fmumap)
mu_dct['fim'] = fmumap
if del_auxilary:
os.remove(fmuref)
os.remove(fmunii)
os.remove(fmu)
return mu_dct