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
# make final mean image meanimg = pp.make_summed_image(tmprealigned) # move data back to main directory nifti_dir, _ = os.path.split(nifti[0]) movedmean = bg.copy_file(meanimg, nifti_dir) # QA if not hasqa: logging.info("qa %s" % subid) qa.plot_movement(tmpparameterfile, subid) # get rid of NAN in files no_nanfiles = pp.clean_nan(tmprealigned) # make 4d volume to visualize movement img4d = qa.make_4d_nibabel(no_nanfiles) bg.zip_files(tmprealigned) # save qa image # qa.save_qa_img(img4d) qa.plot_movement(tmpparameterfile, subid) qa.calc_robust_median_diff(img4d) qa.screen_pet(img4d) # remove tmpfiles bg.remove_files(no_nanfiles) bg.remove_files(newnifti) # coreg pons to pet # find PONS pons_searchstr = "%s/ref_region/pons_tu.nii*" % tracerdir pons = pp.find_single_file(pons_searchstr) if "gz" in pons:
## find sum globstr = os.path.join(s, "pib", "realign_QA", "mean20min*.nii") sum = pp.find_single_file(globstr) if brainmask is None or sum is None: logging.error("pet2mri sum: %s brainmask: %s" % (sum, brainmask)) continue # move dvr and sum to coregdir, unzip if necessary cdvr = bg.copy_file(dvr, coregdir) csum = bg.copy_file(sum, coregdir) cdvr = bg.unzip_file(cdvr) csum = bg.unzip_file(csum) ## coreg pet 2 brainmask corg_out = pp.simple_coregister(str(brainmask), str(csum), other=str(cdvr)) if not corg_out.runtime.returncode == 0: logging.error(corg_out.runtime.traceback) continue rdvr = corg_out.outputs.coregistered_files # copy dvr to freesurfer subjects petdir cdvr = bg.copy_file(rdvr, petdir) globstr = os.path.join(fsdir, "mri", "T1.mgz") t1 = pp.find_single_file(globstr) if t1 is None: logging.error("%s not found" % globstr) continue xfm = fst.fs_generate_dat(cdvr, t1, subid) outfiles = fst.pet_2_surf(cdvr, xfm, mridir) # zip files in coregdir allf = glob("%s/*" % coregdir) bg.zip_files(allf)
# make final mean image meanimg = pp.make_summed_image(tmprealigned) # move data back to main directory nifti_dir, _ = os.path.split(nifti[0]) movedmean = bg.copy_file(meanimg, nifti_dir) #QA if not hasqa: logging.info('qa %s' % subid) qa.plot_movement(tmpparameterfile, subid) # get rid of NAN in files no_nanfiles = pp.clean_nan(tmprealigned) #make 4d volume to visualize movement img4d = qa.make_4d_nibabel(no_nanfiles) bg.zip_files(tmprealigned) #save qa image #qa.save_qa_img(img4d) qa.plot_movement(tmpparameterfile, subid) qa.calc_robust_median_diff(img4d) qa.screen_pet(img4d) #remove tmpfiles bg.remove_files(no_nanfiles) bg.remove_files(newnifti) # coreg pons to pet # find PONS pons_searchstr = '%s/ref_region/pons_tu.nii*' % tracerdir pons = pp.find_single_file(pons_searchstr) if 'gz' in pons:
sum = pp.find_single_file(globstr) if brainmask is None or sum is None: logging.error('pet2mri sum: %s brainmask: %s' % (sum, brainmask)) continue # move dvr and sum to coregdir, unzip if necessary cdvr = bg.copy_file(dvr, coregdir) csum = bg.copy_file(sum, coregdir) cdvr = bg.unzip_file(cdvr) csum = bg.unzip_file(csum) ## coreg pet 2 brainmask corg_out = pp.simple_coregister(str(brainmask), str(csum), other=str(cdvr)) if not corg_out.runtime.returncode == 0: logging.error(corg_out.runtime.traceback) continue rdvr = corg_out.outputs.coregistered_files # copy dvr to freesurfer subjects petdir cdvr = bg.copy_file(rdvr, petdir) globstr = os.path.join(fsdir, 'mri', 'T1.mgz') t1 = pp.find_single_file(globstr) if t1 is None: logging.error('%s not found' % globstr) continue xfm = fst.fs_generate_dat(cdvr, t1, subid) outfiles = fst.pet_2_surf(cdvr, xfm, mridir) # zip files in coregdir allf = glob('%s/*' % coregdir) bg.zip_files(allf)