def transform_vol(invol, xfm, space_defining):
invol = bg.unzip_file(invol) # in case zipped
xfm = bg.unzip_file(xfm) # in case zipped
space_defining = bg.unzip_file(space_defining) # in case zipped
pp.apply_transform_onefile(xfm, invol)
pp.reslice(space_defining, invol)
rinvol = pp.prefix_filename(invol, prefix='r')
bg.remove_files([invol])
bg.zip_files([space_defining])
return rinvol
def transform_vol(invol, xfm, space_defining):
invol = bg.unzip_file(invol)# in case zipped
xfm = bg.unzip_file(xfm)# in case zipped
space_defining = bg.unzip_file(space_defining)# in case zipped
pp.apply_transform_onefile(xfm, invol)
pp.reslice(space_defining, invol)
rinvol = pp.prefix_filename(invol, prefix='r')
bg.remove_files([invol])
bg.zip_files([space_defining])
return rinvol
aparc = glob(globstr)
if not len(aparc) > 0:
logging.error('NO aparcaseg for %s' % globstr)
continue
aparc = aparc[0]
caparc = bg.copy_file(aparc, roidir)
caparc = bg.unzip_file(caparc) # in case zipped
globstr = '%s/coreg_mri2fdg/*.mat*' % pth
xfm = pp.find_single_file(globstr)
if xfm is None:
logging.error('NO transform for %s' % globstr)
continue
cxfm = bg.copy_file(xfm, roidir)
cxfm = bg.unzip_file(cxfm) # in case zipped
pp.apply_transform_onefile(cxfm, caparc)
pp.reslice(dat, caparc)
raparc = pp.prefix_filename(caparc, prefix='r')
data = pp.nibabel.load(dat).get_data()
meand = pp.mean_from_labels(roid, raparc, data)
alld[subid] = meand
###write to file
_, roifname = os.path.split(roifile)
outf = os.path.join(userhome,
'roivalues_%s_%s_%s' % (tracer, cleantime, roifname))
fid = open(outf, 'w+')
fid.write('SUBID,')
rois = sorted(meand.keys())
roiss = ','.join(rois)
fid.write(roiss)
shutil.rmtree(coregdir)
continue
cbrainmask = bg.copy_file(brainmask, coregdir)
cbrainmask = bg.unzip_file(cbrainmask)
# aparc aseg
globstr = os.path.join(basedir, 'anatomy', '*aparc_aseg.nii*')
aparc = pp.find_single_file(globstr)
if aparc is None:
logging.error('%s not found. skipping' % globstr)
shutil.rmtree(coregdir)
continue
caparc = bg.copy_file(aparc, coregdir)
caparc = bg.unzip_file(caparc)
# cerebellum
globstr = os.path.join(pth, 'ref_region', 'grey_cerebellum.nii*')
cere = pp.find_single_file(globstr)
if cere is None:
logging.error('%s not found. skipping' % globstr)
shutil.rmtree(coregdir)
continue
ccere = bg.copy_file(cere, coregdir)
ccere = bg.unzip_file(ccere)
# have all out files, coreg
xfm = os.path.join(coregdir, 'mri_to_pet.mat')
corgout = pp.invert_coreg(cbrainmask, mean_20min, xfm)
pp.reslice(mean_20min, cbrainmask)
pp.apply_transform_onefile(xfm, ccere)
pp.reslice(mean_20min, ccere)
pp.apply_transform_onefile(xfm, caparc)
pp.reslice(mean_20min, caparc)
cbrainmask = bg.unzip_file(cbrainmask)
# aparc aseg
globstr = os.path.join(basedir, 'anatomy', '*aparc_aseg.nii*')
aparc = pp.find_single_file(globstr)
if aparc is None:
logging.error('%s not found. skipping'%globstr)
shutil.rmtree(coregdir)
continue
caparc = bg.copy_file(aparc, coregdir)
caparc = bg.unzip_file(caparc)
# cerebellum
globstr = os.path.join(pth, 'ref_region', 'grey_cerebellum.nii*')
cere = pp.find_single_file(globstr)
if cere is None:
logging.error('%s not found. skipping'%globstr)
shutil.rmtree(coregdir)
continue
ccere = bg.copy_file(cere, coregdir)
ccere = bg.unzip_file(ccere)
# have all out files, coreg
xfm = os.path.join(coregdir, 'mri_to_pet.mat')
corgout = pp.invert_coreg(cbrainmask, mean_20min,xfm)
pp.reslice(mean_20min, cbrainmask)
pp.apply_transform_onefile(xfm, ccere)
pp.reslice(mean_20min, ccere)
pp.apply_transform_onefile(xfm, caparc)
pp.reslice(mean_20min, caparc)
caparc = bg.copy_file(aparc, coreg_dir)
xfm_file = pp.make_transform_name(cpet, cmri)
logging.info("coreg %s" % (subid))
corg_out = pp.invert_coreg(cmri, cpet, xfm_file)
if not corg_out.runtime.returncode == 0:
logging.warning(corg_out.runtime.stderr)
continue
apply_out = pp.apply_transform_onefile(xfm_file, cpons)
if not apply_out.runtime.returncode == 0:
logging.warning(apply_out.runtime.stderr)
continue
apply_out = pp.apply_transform_onefile(xfm_file, caparc)
if not apply_out.runtime.returncode == 0:
logging.warning(apply_out.runtime.stderr)
continue
rout_mri = pp.reslice(cpet, cmri)
if not rout_mri.runtime.returncode == 0:
logging.warning(rout_mri.runtime.stderr)
else:
rmri = pp.prefix_filename(cmri, prefix="r")
_, rmri_nme = os.path.split(rmri)
new_rmri = rmri_nme.replace("rbr", "rfdg_br")
newmri = bg.copy_file(rmri, "%s/anatomy/%s" % (sub, new_rmri))
if newmri:
bg.remove_files([cmri, rmri])
rout_pons = pp.reslice(cpet, cpons)
if not rout_pons.runtime.returncode == 0:
logging.warning(rout_pons.runtime.stderr)
else:
rpons = pp.prefix_filename(cpons, prefix="r")
newpons = bg.copy_file(rpons, "%s/ref_region" % (tracerdir))
aparc = glob(globstr)
if not len(aparc)>0:
logging.error('NO aparcaseg for %s'%globstr)
continue
aparc = aparc[0]
caparc = bg.copy_file(aparc, roidir)
caparc = bg.unzip_file(caparc)# in case zipped
globstr = '%s/coreg_mri2fdg/*.mat*'%pth
xfm = pp.find_single_file(globstr)
if xfm is None:
logging.error('NO transform for %s'%globstr)
continue
cxfm = bg.copy_file(xfm, roidir)
cxfm = bg.unzip_file(cxfm)# in case zipped
pp.apply_transform_onefile(cxfm, caparc)
pp.reslice(dat, caparc)
raparc = pp.prefix_filename(caparc, prefix='r')
data = pp.nibabel.load(dat).get_data()
meand = pp.mean_from_labels(roid, raparc, data)
alld[subid] = meand
###write to file
_, roifname = os.path.split(roifile)
outf = os.path.join(userhome, 'roivalues_%s_%s_%s'%(tracer,
cleantime,
roifname))
fid =open(outf, 'w+')
fid.write('SUBID,')
rois = sorted(meand.keys())
caparc = bg.copy_file(aparc, coreg_dir)
xfm_file = pp.make_transform_name(cpet, cmri)
logging.info('coreg %s' % (subid))
corg_out = pp.invert_coreg(cmri, cpet, xfm_file)
if not corg_out.runtime.returncode == 0:
logging.warning(corg_out.runtime.stderr)
continue
apply_out = pp.apply_transform_onefile(xfm_file, cpons)
if not apply_out.runtime.returncode == 0:
logging.warning(apply_out.runtime.stderr)
continue
apply_out = pp.apply_transform_onefile(xfm_file, caparc)
if not apply_out.runtime.returncode == 0:
logging.warning(apply_out.runtime.stderr)
continue
rout_mri = pp.reslice(cpet, cmri)
if not rout_mri.runtime.returncode == 0:
logging.warning(rout_mri.runtime.stderr)
else:
rmri = pp.prefix_filename(cmri, prefix='r')
_, rmri_nme = os.path.split(rmri)
new_rmri = rmri_nme.replace('rbr', 'rfdg_br')
newmri = bg.copy_file(rmri, '%s/anatomy/%s' % (sub, new_rmri))
if newmri:
bg.remove_files([cmri, rmri])
rout_pons = pp.reslice(cpet, cpons)
if not rout_pons.runtime.returncode == 0:
logging.warning(rout_pons.runtime.stderr)
else:
rpons = pp.prefix_filename(cpons, prefix='r')
newpons = bg.copy_file(rpons, '%s/ref_region' % (tracerdir))
