def test_nrrd2nifti(self): PREFIX = pjoin(outdir, 'nrrd2nifti_prefix') # run nrrd2nifti conversion conversion.nifti_write(REFERENCE_NRRD, PREFIX) # load converted output converted_nifti = load(PREFIX + '.nii.gz') converted_nifti_data = converted_nifti.get_data() converted_nifti_affine = converted_nifti.affine converted_nifti_bvals = conversion.read_bvals(PREFIX + '.bval') converted_nifti_bvecs = conversion.read_bvecs(PREFIX + '.bvec') # load converted reference converted_nifti = load(CONVERTED_NIFTI) reference_nifti_data = converted_nifti.get_data() reference_nifti_affine = converted_nifti.affine reference_nifti_bvals = conversion.read_bvals(CONVERTED_BVAL) reference_nifti_bvecs = conversion.read_bvecs(CONVERTED_BVEC) # test equality testing.assert_array_equal(reference_nifti_data, converted_nifti_data) testing.assert_array_equal(reference_nifti_affine, converted_nifti_affine) testing.assert_array_equal(reference_nifti_bvals, converted_nifti_bvals) testing.assert_array_equal(reference_nifti_bvecs, converted_nifti_bvecs)
def bval_bvec_difference(imgPath_given_mat, imgPath_given_py, caselist): bval_diff_list = [] bval_total_diff = [] bval_mean_diff = [] bvec_diff_list = [] bvec_total_diff = [] bvec_mean_diff = [] for case in caselist: imgPath_mat = imgPath_given_mat.replace('XYZ', case) imgPath_py = imgPath_given_py.replace('XYZ', case) # load python bvals_py = np.array(read_bvals(imgPath_py.split('.nii')[0] + '.bval')) bvecs_py = np.array(read_bvecs(imgPath_py.split('.nii')[0] + '.bvec')) bvals_py, bvecs_py = stack_one_b0(bvals_py, bvecs=bvecs_py) bvals_py = bvals_py.astype('float64') bvecs_py = bvecs_py.astype('float64') # load matlab bvals_mat = np.array( read_bvals(imgPath_mat.split('.nii')[0] + '.bval')) bvecs_mat = np.array( read_bvecs(imgPath_mat.split('.nii')[0] + '.bvec')) bvals_mat = bvals_mat.astype('float64') bvecs_mat = bvecs_mat.astype('float64') # obtain case wise difference for bvals diff = 2 * abs(bvals_py - bvals_mat) / (bvals_py + bvals_mat) * 100 bval_diff_list.append(diff.flatten()) bval_mean_diff.append(diff.mean()) # obtain case wise difference diff = 2 * abs(bvecs_py - bvecs_mat) / (bvals_py + bvals_mat) * 100 bvec_diff_list.append(diff.flatten()) bvec_mean_diff.append(diff.mean()) print( f'Mean of mean relative percentage difference over all the bvals: {np.mean(bval_mean_diff)}' ) hist_calc(bval_diff_list, bins=BINS) print('\n\n') print( f'Mean of mean relative percentage difference over all the bvecs: {np.mean(bvec_mean_diff)}' ) hist_calc(bvec_diff_list, bins=BINS) print('\n\n')
def separateBshells(imgPath, ref_bvals_file=None, ref_bvals=None): if ref_bvals_file: print('Reading reference b-shell file ...') ref_bvals = read_bvals(ref_bvals_file) print('Separating b-shells for', imgPath) imgPath = local.path(imgPath) img = load(imgPath._path) dwi = img.get_data() inPrefix = abspath(imgPath).split('.nii')[0] bvals = np.array(read_bvals(inPrefix + '.bval')) bvecs = np.array(read_bvecs(inPrefix + '.bvec')) for bval in ref_bvals: # ind= np.where(bval==bvals)[0] ind = np.where(abs(bval - bvals) <= BSHELL_MIN_DIST)[0] N_b = len(ind) bPrefix = inPrefix + f'_b{int(bval)}' if bval == 0.: b0 = find_b0(dwi, ind) else: b0_bshell = np.zeros( (dwi.shape[0], dwi.shape[1], dwi.shape[2], N_b + 1), dtype='float32') b0_bshell[:, :, :, 0] = b0 b0_bshell[:, :, :, 1:] = dwi[:, :, :, ind] b0_bvals = [0.] + [bval] * N_b b0_bvecs = np.zeros((N_b + 1, 3), dtype='float32') b0_bvecs[1:, ] = bvecs[ind, :] bshell_written = load(bPrefix + '.nii.gz').get_fdata() bvals_written = read_bvals(bPrefix + '.bval') bvecs_written = read_bvecs(bPrefix + '.bvec') print('bshell difference', abs(b0_bshell - bshell_written).sum()) print('bvals difference', (np.array(b0_bvals) - np.array(bvals_written)).sum()) print('bvecs difference', (np.array(b0_bvecs) - np.array(bvecs_written)).sum())
def separateBshells(imgPath, ref_bvals_file=None, ref_bvals=None): if ref_bvals_file: print('Reading reference b-shell file ...') ref_bvals = read_bvals(ref_bvals_file) print('Separating b-shells for', imgPath) imgPath = local.path(imgPath) img = load(imgPath._path) dwi = img.get_data() inPrefix = abspath(imgPath).split('.nii')[0] bvals = np.array(read_bvals(inPrefix + '.bval')) bvecs = np.array(read_bvecs(inPrefix + '.bvec')) for bval in ref_bvals: # ind= np.where(bval==bvals)[0] ind = np.where(abs(bval - bvals) <= BSHELL_MIN_DIST)[0] N_b = len(ind) bPrefix = inPrefix + f'_b{int(bval)}' if bval == 0.: b0 = find_b0(dwi, ind) if isfile(bPrefix + '.nii.gz'): continue if bval == 0.: save_nifti(bPrefix + '.nii.gz', b0, img.affine, img.header) else: b0_bshell = np.zeros( (dwi.shape[0], dwi.shape[1], dwi.shape[2], N_b + 1), dtype='float32') b0_bshell[:, :, :, 0] = b0 b0_bshell[:, :, :, 1:] = dwi[:, :, :, ind] b0_bvals = [0.] + [bval] * N_b b0_bvecs = np.zeros((N_b + 1, 3), dtype='float32') b0_bvecs[1:, ] = bvecs[ind, :] save_nifti(bPrefix + '.nii.gz', b0_bshell, img.affine, img.header) write_bvals(bPrefix + '.bval', b0_bvals) write_bvecs(bPrefix + '.bvec', b0_bvecs)
def main(self): # if self.force: # logging.info('Deleting previous output directory') # rm('-rf', self.outDir) temp= self.dwi_file.split(',') primaryVol= abspath(temp[0]) if len(temp)<2: raise AttributeError('Two volumes are required for --imain') else: secondaryVol= abspath(temp[1]) if self.b0_brain_mask: temp = self.b0_brain_mask.split(',') primaryMask = abspath(temp[0]) if len(temp) == 2: secondaryMask = abspath(temp[1]) else: secondaryMask = abspath(temp[0]) else: primaryMask=[] secondaryMask=[] # obtain 4D/3D info and time axis info dimension = load_nifti(primaryVol).header['dim'] dim1 = dimension[0] if dim1!=4: raise AttributeError('primary volume must be 4D, however, secondary can be 3D/4D') numVol1 = dimension[4] dimension = load_nifti(secondaryVol).header['dim'] dim2 = dimension[0] numVol2 = dimension[4] temp= self.bvals_file.split(',') if len(temp)>=1: primaryBval= abspath(temp[0]) if len(temp)==2: secondaryBval= abspath(temp[1]) elif len(temp)==1 and dim2==4: secondaryBval= primaryBval elif len(temp)==1 and dim2==3: secondaryBval=[] elif len(temp)==0: raise AttributeError('--bvals are required') temp= self.bvecs_file.split(',') if len(temp)>=1: primaryBvec= abspath(temp[0]) if len(temp)==2: secondaryBvec= abspath(temp[1]) elif len(temp) == 1 and dim2 == 4: secondaryBvec = primaryBvec elif len(temp)==1 and dim2==3: secondaryBvec=[] else: raise AttributeError('--bvecs are required') with TemporaryDirectory() as tmpdir: tmpdir= local.path(tmpdir) # mask both volumes, fslmaths can do that irrespective of dimension logging.info('Masking the volumes') primaryMaskedVol = tmpdir / 'primaryMasked.nii.gz' secondaryMaskedVol = tmpdir / 'secondaryMasked.nii.gz' if primaryMask: # mask the volume fslmaths[primaryVol, '-mas', primaryMask, primaryMaskedVol] & FG else: primaryMaskedVol= primaryVol if secondaryMask: # mask the volume fslmaths[secondaryVol, '-mas', secondaryMask, secondaryMaskedVol] & FG else: secondaryMaskedVol= secondaryVol logging.info('Extracting B0 from masked volumes') B0_PA= tmpdir / 'B0_PA.nii.gz' B0_AP= tmpdir / 'B0_AP.nii.gz' obtainB0(primaryMaskedVol, primaryBval, B0_PA, self.num_b0) if dim2==4: obtainB0(secondaryMaskedVol, secondaryBval, B0_AP, self.num_b0) else: B0_AP= secondaryMaskedVol B0_PA_AP_merged = tmpdir / 'B0_PA_AP_merged.nii.gz' with open(self.acqparams_file._path) as f: acqp= f.read().split('\n') logging.info('Writing acqparams.txt for topup') # firstDim: first acqp line should be replicated this number of times firstB0dim= load_nifti(str(B0_PA)).header['dim'][4] # secondDim: second acqp line should be replicated this number of times secondB0dim= load_nifti(str(B0_AP)).header['dim'][4] acqp_topup= tmpdir / 'acqp_topup.txt' with open(acqp_topup,'w') as f: for i in range(firstB0dim): f.write(acqp[0]+'\n') for i in range(secondB0dim): f.write(acqp[1]+'\n') logging.info('Merging B0_PA and BO_AP') fslmerge('-t', B0_PA_AP_merged, B0_PA, B0_AP) topup_params, applytopup_params, eddy_openmp_params= obtain_fsl_eddy_params(self.eddy_config_file._path) # Example for topup # === on merged b0 images === # https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy/UsersGuide#Running_topup_on_the_b.3D0_volumes # topup --imain=both_b0 --datain=my_acq_param.txt --out=my_topup_results # === on all b0 images === # https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/topup/TopupUsersGuide#Running_topup # topup --imain=all_my_b0_images.nii --datain=acquisition_parameters.txt --config=b02b0.cnf --out=my_output logging.info('Running topup') topup_results= tmpdir / 'topup_results' topup[f'--imain={B0_PA_AP_merged}', f'--datain={acqp_topup}', f'--out={topup_results}', '--verbose', topup_params.split()] & FG logging.info('Running applytopup') topupMask= tmpdir / 'topup_mask.nii.gz' # applytopup on primary4D,secondary4D/3D topupOut= tmpdir / 'topup_out.nii.gz' if dim2==4: applytopup[f'--imain={primaryMaskedVol},{secondaryMaskedVol}', f'--datain={self.acqparams_file}', '--inindex=1,2', f'--topup={topup_results}', f'--out={topupOut}', '--verbose', applytopup_params.split()] & FG else: applytopup[f'--imain={B0_PA},{B0_AP}', f'--datain={self.acqparams_file}', '--inindex=1,2', f'--topup={topup_results}', f'--out={topupOut}', '--verbose', applytopup_params.split()] & FG topupOutMean= tmpdir / 'topup_out_mean.nii.gz' fslmaths[topupOut, '-Tmean', topupOutMean] & FG bet[topupOutMean, topupMask._path.split('_mask.nii.gz')[0], '-m', '-n'] & FG # another approach could be # threshold mean of primary,secondary mask at 0.5 and obtain modified mask, use that mask for eddy_openmp # fslmerge[topupMask, '-t', primaryMask, secondaryMask] & FG # fslmaths[topupMask, '-Tmean', topupMask] & FG # fslmaths[topupMask, '-thr', '0.5', topupMask, '-odt' 'char'] & FG logging.info('Writing index.txt for topup') indexFile= tmpdir / 'index.txt' with open(indexFile, 'w') as f: for i in range(numVol1): f.write('1\n') outPrefix = tmpdir / basename(primaryVol).split('.')[0] + '_Ep_Ed' temp = self.whichVol.split(',') if len(temp)==1 and temp[0]=='1': # correct only primary4D volume eddy_openmp[f'--imain={primaryMaskedVol}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={primaryBvec}', f'--bvals={primaryBval}', f'--out={outPrefix}', f'--topup={topup_results}', '--verbose', eddy_openmp_params.split()] & FG elif len(temp)==2 and temp[1]=='2': # sylvain would like to correct both primary and secondary volumes with open(indexFile, 'a') as f: for i in range(numVol2): f.write('2\n') # join both bvalFiles bvals1= read_bvals(primaryBval) if dim2==4 and not secondaryBval: bvals2= bvals1.copy() elif dim2==4 and secondaryBval: bvals2= read_bvals(secondaryBval) elif dim2==3: bvals2=[0] combinedBvals = tmpdir / 'combinedBvals.txt' write_bvals(combinedBvals, bvals1+bvals2) # join both bvecFiles bvecs1= read_bvecs(primaryBvec) if dim2==4 and not secondaryBvec: bvecs2= bvecs1.copy() elif dim2==4 and secondaryBvec: bvecs2= read_bvecs(secondaryBvec) elif dim2==3: bvecs2=[[0,0,0]] # join both bvecFiles combinedBvecs = tmpdir / 'combinedBvecs.txt' write_bvecs(combinedBvecs, bvecs1+bvecs2) combinedData= tmpdir / 'combinedData.nii.gz' fslmerge('-t', combinedData, primaryMaskedVol, secondaryMaskedVol) eddy_openmp[f'--imain={combinedData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={combinedBvecs}', f'--bvals={combinedBvals}', f'--out={outPrefix}', f'--topup={topup_results}', '--verbose', eddy_openmp_params.split()] & FG else: raise ValueError('Invalid --whichVol') # copy bval,bvec to have same prefix as that of eddy corrected volume copyfile(outPrefix+'.eddy_rotated_bvecs', outPrefix+'.bvec') copyfile(primaryBval, outPrefix+'.bval') # rename topupMask to have same prefix as that of eddy corrected volume topupMask.move(outPrefix+'_mask.nii.gz') tmpdir.move(self.outDir)
def main(self): self.out = local.path(self.out) if self.out.exists(): if self.overwrite: self.out.delete() else: logging.error("{} exists, use '--force' to overwrite it".format(self.out)) sys.exit(1) outxfms = self.out.dirname / self.out.stem+'_xfms.tgz' with TemporaryDirectory() as tmpdir, local.cwd(tmpdir): tmpdir = local.path(tmpdir) dicePrefix = 'vol' logging.info('Dice the DWI') fslsplit[self.dwi] & FG logging.info('Extract the B0') check_call((' ').join([pjoin(FILEDIR,'bse.py'), '-i', self.dwi._path, '-o', 'b0.nii.gz']), shell= True) logging.info('Register each volume to the B0') vols = sorted(tmpdir // (dicePrefix + '*.nii.gz')) # use the following multi-processed loop pool= Pool(int(self.nproc)) res= pool.map_async(_Register_vol, vols) volsRegistered= res.get() pool.close() pool.join() # or use the following for loop # volsRegistered = [] # for vol in vols: # volnii = vol.with_suffix('.nii.gz') # logging.info('Run FSL flirt affine registration') # flirt('-interp' ,'sinc' # ,'-sincwidth' ,'7' # ,'-sincwindow' ,'blackman' # ,'-in', volnii # ,'-ref', 'b0.nii.gz' # ,'-nosearch' # ,'-o', volnii # ,'-omat', volnii.with_suffix('.txt', depth=2) # ,'-paddingsize', '1') # volsRegistered.append(volnii) fslmerge('-t', 'EddyCorrect-DWI.nii.gz', volsRegistered) transforms = tmpdir.glob(dicePrefix+'*.txt') transforms.sort() logging.info('Extract the rotations and realign the gradients') bvecs= read_bvecs(self.bvecFile._path) bvecs_new= bvecs.copy() for (i,t) in enumerate(transforms): logging.info('Apply ' + t) tra = np.loadtxt(t) # removes the translation aff = np.matrix(tra[0:3,0:3]) # computes the finite strain of aff to get the rotation rot = aff*aff.T # compute the square root of rot [el, ev] = np.linalg.eig(rot) eL = np.identity(3)*np.sqrt(el) sq = ev*eL*ev.I # finally the rotation is defined as rot = sq.I*aff bvecs_new[i] = np.dot(rot,bvecs[i]).tolist()[0] tar('cvzf', outxfms, transforms) # save modified bvecs write_bvecs(self.out._path+'.bvec', bvecs_new) # save EddyCorrect-DWI local.path('EddyCorrect-DWI.nii.gz').copy(self.out._path+'.nii.gz') # copy bvals self.bvalFile.copy(self.out._path+'.bval') if self.debug: tmpdir.copy(pjoin(dirname(self.out),"eddy-debug-"+str(getpid())))
def _eddy_openmp(modData, modBvals, modBvecs, eddy_openmp_params): print('eddy_openmp/cuda parameters') print(eddy_openmp_params) print('') # eddy_openmp yields as many volumes as there are input volumes # this is the main output and consists of the input data after correction for # eddy currents, subject movement, and susceptibility if --topup was specified eddy_openmp[f'--imain={modData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={modBvecs}', f'--bvals={modBvals}', f'--out={outPrefix}', f'--topup={topup_results}', eddy_openmp_params.split()] & FG # free space, see https://github.com/pnlbwh/pnlNipype/issues/82 if '--repol' in eddy_openmp_params: rm[f'{outPrefix}.eddy_outlier_free_data.nii.gz'] & FG bvals = np.array(read_bvals(modBvals)) ind= [i for i in range(len(bvals)) if bvals[i]>B0_THRESHOLD and bvals[i]<= REPOL_BSHELL_GREATER] if '--repol' in eddy_openmp_params and len(ind): print('\nDoing eddy_openmp/cuda again without --repol option ' f'to obtain eddy correction w/o outlier replacement for b<={REPOL_BSHELL_GREATER} shells\n') eddy_openmp_params = eddy_openmp_params.split() eddy_openmp_params.remove('--repol') print(eddy_openmp_params) print('') wo_repol_outDir = local.path(outPrefix).dirname.join('wo_repol') wo_repol_outDir.mkdir() wo_repol_outPrefix = pjoin(wo_repol_outDir, basename(outPrefix)) eddy_openmp[f'--imain={modData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={modBvecs}', f'--bvals={modBvals}', f'--out={wo_repol_outPrefix}', f'--topup={topup_results}', eddy_openmp_params] & FG repol_bvecs = np.array(read_bvecs(outPrefix + '.eddy_rotated_bvecs')) wo_repol_bvecs = np.array(read_bvecs(wo_repol_outPrefix + '.eddy_rotated_bvecs')) merged_bvecs = repol_bvecs.copy() merged_bvecs[ind, :] = wo_repol_bvecs[ind, :] repol_data = load_nifti(outPrefix + '.nii.gz') wo_repol_data = load_nifti(wo_repol_outPrefix + '.nii.gz') merged_data = repol_data.get_fdata().copy() merged_data[..., ind] = wo_repol_data.get_fdata()[..., ind] save_nifti(outPrefix + '.nii.gz', merged_data, repol_data.affine, hdr=repol_data.header) # copy bval,bvec to have same prefix as that of eddy corrected volume write_bvecs(outPrefix + '.bvec', merged_bvecs) copyfile(modBvals, outPrefix + '.bval') # clean up rm['-r', wo_repol_outDir] & FG else: # copy bval,bvec to have same prefix as that of eddy corrected volume copyfile(outPrefix + '.eddy_rotated_bvecs', outPrefix + '.bvec') copyfile(modBvals, outPrefix + '.bval')
def main(self): from plumbum.cmd import eddy_openmp # cli.NonexistentPath is already making sure it does not exist self.outDir.mkdir() if self.useGpu: try: from plumbum.cmd import nvcc nvcc['--version'] & FG print('\nCUDA found, looking for available GPU\n') from GPUtil import getFirstAvailable getFirstAvailable() print('available GPU found, looking for eddy_cuda executable\n' 'make sure you have created a softlink according to ' 'https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy/UsersGuide') from plumbum.cmd import eddy_cuda as eddy_openmp print('\neddy_cuda executable found\n') except: print('nvcc, available GPU, and/or eddy_cuda was not found, using eddy_openmp') def _eddy_openmp(modData, modBvals, modBvecs, eddy_openmp_params): print('eddy_openmp/cuda parameters') print(eddy_openmp_params) print('') # eddy_openmp yields as many volumes as there are input volumes # this is the main output and consists of the input data after correction for # eddy currents, subject movement, and susceptibility if --topup was specified eddy_openmp[f'--imain={modData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={modBvecs}', f'--bvals={modBvals}', f'--out={outPrefix}', f'--topup={topup_results}', eddy_openmp_params.split()] & FG # free space, see https://github.com/pnlbwh/pnlNipype/issues/82 if '--repol' in eddy_openmp_params: rm[f'{outPrefix}.eddy_outlier_free_data.nii.gz'] & FG bvals = np.array(read_bvals(modBvals)) ind= [i for i in range(len(bvals)) if bvals[i]>B0_THRESHOLD and bvals[i]<= REPOL_BSHELL_GREATER] if '--repol' in eddy_openmp_params and len(ind): print('\nDoing eddy_openmp/cuda again without --repol option ' f'to obtain eddy correction w/o outlier replacement for b<={REPOL_BSHELL_GREATER} shells\n') eddy_openmp_params = eddy_openmp_params.split() eddy_openmp_params.remove('--repol') print(eddy_openmp_params) print('') wo_repol_outDir = local.path(outPrefix).dirname.join('wo_repol') wo_repol_outDir.mkdir() wo_repol_outPrefix = pjoin(wo_repol_outDir, basename(outPrefix)) eddy_openmp[f'--imain={modData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={modBvecs}', f'--bvals={modBvals}', f'--out={wo_repol_outPrefix}', f'--topup={topup_results}', eddy_openmp_params] & FG repol_bvecs = np.array(read_bvecs(outPrefix + '.eddy_rotated_bvecs')) wo_repol_bvecs = np.array(read_bvecs(wo_repol_outPrefix + '.eddy_rotated_bvecs')) merged_bvecs = repol_bvecs.copy() merged_bvecs[ind, :] = wo_repol_bvecs[ind, :] repol_data = load_nifti(outPrefix + '.nii.gz') wo_repol_data = load_nifti(wo_repol_outPrefix + '.nii.gz') merged_data = repol_data.get_fdata().copy() merged_data[..., ind] = wo_repol_data.get_fdata()[..., ind] save_nifti(outPrefix + '.nii.gz', merged_data, repol_data.affine, hdr=repol_data.header) # copy bval,bvec to have same prefix as that of eddy corrected volume write_bvecs(outPrefix + '.bvec', merged_bvecs) copyfile(modBvals, outPrefix + '.bval') # clean up rm['-r', wo_repol_outDir] & FG else: # copy bval,bvec to have same prefix as that of eddy corrected volume copyfile(outPrefix + '.eddy_rotated_bvecs', outPrefix + '.bvec') copyfile(modBvals, outPrefix + '.bval') # if self.force: # logging.info('Deleting previous output directory') # rm('-rf', self.outDir) temp= self.dwi_file.split(',') primaryVol= abspath(temp[0]) if len(temp)<2: raise AttributeError('Two volumes are required for --imain') else: secondaryVol= abspath(temp[1]) primaryMask=[] secondaryMask=[] if self.b0_brain_mask: temp = self.b0_brain_mask.split(',') primaryMask = abspath(temp[0]) if len(temp) == 2: secondaryMask = abspath(temp[1]) # obtain 4D/3D info and time axis info dimension = load_nifti(primaryVol).header['dim'] dim1 = dimension[0] if dim1!=4: raise AttributeError('Primary volume must be 4D, however, secondary can be 3D/4D') numVol1 = dimension[4] dimension = load_nifti(secondaryVol).header['dim'] dim2 = dimension[0] numVol2 = dimension[4] temp= self.bvals_file.split(',') if len(temp)>=1: primaryBval= abspath(temp[0]) if len(temp)==2: secondaryBval= abspath(temp[1]) elif len(temp)==1 and dim2==4: secondaryBval= primaryBval elif len(temp)==1 and dim2==3: secondaryBval=[] elif len(temp)==0: raise AttributeError('--bvals are required') temp= self.bvecs_file.split(',') if len(temp)>=1: primaryBvec= abspath(temp[0]) if len(temp)==2: secondaryBvec= abspath(temp[1]) elif len(temp) == 1 and dim2 == 4: secondaryBvec = primaryBvec elif len(temp)==1 and dim2==3: secondaryBvec=[] else: raise AttributeError('--bvecs are required') with local.cwd(self.outDir): # mask both volumes, fslmaths can do that irrespective of dimension logging.info('Masking the volumes') primaryMaskedVol = 'primary_masked.nii.gz' secondaryMaskedVol = 'secondary_masked.nii.gz' if primaryMask: # mask the volume fslmaths[primaryVol, '-mas', primaryMask, primaryMaskedVol] & FG else: primaryMaskedVol= primaryVol if secondaryMask: # mask the volume fslmaths[secondaryVol, '-mas', secondaryMask, secondaryMaskedVol] & FG else: secondaryMaskedVol= secondaryVol logging.info('Extracting B0 from masked volumes') B0_PA= 'B0_PA.nii.gz' B0_AP= 'B0_AP.nii.gz' obtainB0(primaryMaskedVol, primaryBval, B0_PA, self.num_b0) if dim2==4: obtainB0(secondaryMaskedVol, secondaryBval, B0_AP, self.num_b0) else: B0_AP= secondaryMaskedVol B0_PA_AP_merged = 'B0_PA_AP_merged.nii.gz' with open(self.acqparams_file._path) as f: acqp= f.read().strip().split('\n') if len(acqp)!=2: raise ValueError('The acquisition parameter file must have exactly two lines') logging.info('Writing acqparams.txt for topup') # firstDim: first acqp line should be replicated this number of times firstB0dim= load_nifti(str(B0_PA)).header['dim'][4] # secondDim: second acqp line should be replicated this number of times secondB0dim= load_nifti(str(B0_AP)).header['dim'][4] acqp_topup= 'acqp_topup.txt' with open(acqp_topup,'w') as f: for i in range(firstB0dim): f.write(acqp[0]+'\n') for i in range(secondB0dim): f.write(acqp[1]+'\n') logging.info('Merging B0_PA and BO_AP') fslmerge('-t', B0_PA_AP_merged, B0_PA, B0_AP) topup_params, applytopup_params, eddy_openmp_params= obtain_fsl_eddy_params(self.eddy_config_file._path) # Example for topup # === on merged b0 images === # https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy/UsersGuide#Running_topup_on_the_b.3D0_volumes # topup --imain=P2A_A2P_b0 --datain=acqparams.txt --config=b02b0.cnf --out=my_output --iout=my_output # # === on all b0 images === # https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/topup/TopupUsersGuide#Running_topup # topup --imain=all_b0s --datain=acqparams.txt --config=b02b0.cnf --out=my_output --iout=my_output logging.info('Running topup') topup_results= 'topup_out' topupOut= 'topup_out.nii.gz' # topup --iout yields as many volumes as there are input volumes # --iout specifies the name of a 4D image file that contains unwarped and movement corrected images. # each volume in the --imain will have a corresponding corrected volume in --iout. # --iout is used for creating modified mask only # when primary4D,secondary4D/3D are already masked, this will be useful topup[f'--imain={B0_PA_AP_merged}', f'--datain={acqp_topup}', f'--out={topup_results}', f'--iout={topupOut}', topup_params.split()] & FG # provide topupOutMean for quality checking topupOutMean= 'topup_out_mean.nii.gz' fslmaths[topupOut, '-Tmean', topupOutMean] & FG logging.info('Running applytopup') # applytopup always yields one output file regardless of one or two input files # if two input files are provided, the resulting undistorted file will be a combination of the two # containing only as many volumes as there are in one file # B0_PA_correct, B0_AP_correct are for quality checking only # primaryMaskCorrect, secondaryMaskCorrect will be associated masks B0_PA_correct= 'B0_PA_corrected.nii.gz' applytopup[f'--imain={B0_PA}', f'--datain={self.acqparams_file}', '--inindex=1', f'--topup={topup_results}', f'--out={B0_PA_correct}', applytopup_params.split()] & FG B0_AP_correct= 'B0_AP_corrected.nii.gz' applytopup[f'--imain={B0_AP}', f'--datain={self.acqparams_file}', '--inindex=2', f'--topup={topup_results}', f'--out={B0_AP_correct}', applytopup_params.split()] & FG B0_PA_AP_corrected_merged= 'B0_PA_AP_corrected_merged' fslmerge('-t', B0_PA_AP_corrected_merged, B0_PA_correct, B0_AP_correct) fslmaths[B0_PA_AP_corrected_merged, '-Tmean', 'B0_PA_AP_corrected_mean'] & FG topupMask= 'topup_mask.nii.gz' # calculate topup mask if primaryMask and secondaryMask: fslmaths[primaryMask, '-mul', '1', primaryMask, '-odt', 'float'] fslmaths[secondaryMask, '-mul', '1', secondaryMask, '-odt', 'float'] applytopup_params+=' --interp=trilinear' # this straightforward way could be used ''' applytopup[f'--imain={primaryMask},{secondaryMask}', f'--datain={self.acqparams_file}', '--inindex=1,2', f'--topup={topup_results}', f'--out={topupMask}', applytopup_params.split()] & FG ''' # but let's do it step by step in order to have more control of the process # binarise the mean of corrected primary,secondary mask to obtain modified mask # use that mask for eddy_openmp primaryMaskCorrect = 'primary_mask_corrected.nii.gz' applytopup[f'--imain={primaryMask}', f'--datain={self.acqparams_file}', '--inindex=1', f'--topup={topup_results}', f'--out={primaryMaskCorrect}', applytopup_params.split()] & FG secondaryMaskCorrect = 'secondary_mask_corrected.nii.gz' applytopup[f'--imain={secondaryMask}', f'--datain={self.acqparams_file}', '--inindex=2', f'--topup={topup_results}', f'--out={secondaryMaskCorrect}', applytopup_params.split()] & FG fslmerge('-t', topupMask, primaryMaskCorrect, secondaryMaskCorrect) temp= load_nifti(topupMask) data= temp.get_fdata() data= abs(data[...,0])+ abs(data[...,1]) data[data!=0]= 1 # filter the mask to smooth edges # scale num of erosion followed by scale num of dilation # the greater the scale, the smoother the edges # scale=2 seems sufficient data= single_scale(data, int(self.scale)) save_nifti(topupMask, data.astype('uint8'), temp.affine, temp.header) else: # this block assumes the primary4D,secondary4D/3D are already masked # then toupOutMean is also masked # binarise the topupOutMean to obtain modified mask # use that mask for eddy_openmp # fslmaths[topupOutMean, '-bin', topupMask, '-odt', 'char'] & FG # if --mask is not provided at all, this block creates a crude mask # apply bet on the mean of topup output to obtain modified mask # use that mask for eddy_openmp bet[topupOutMean, topupMask.split('_mask.nii.gz')[0], '-m', '-n'] & FG logging.info('Writing index.txt for topup') indexFile= 'index.txt' with open(indexFile, 'w') as f: for i in range(numVol1): f.write('1\n') outPrefix = basename(primaryVol).split('.nii')[0] # remove _acq- outPrefix= outPrefix.replace('_acq-PA','') outPrefix= outPrefix.replace('_acq-AP','') # find dir field if '_dir-' in primaryVol and '_dir-' in secondaryVol and self.whichVol == '1,2': dir= load_nifti(primaryVol).shape[3]+ load_nifti(secondaryVol).shape[3] outPrefix= local.path(re.sub('_dir-(.+?)_', f'_dir-{dir}_', outPrefix)) outPrefix = outPrefix + '_EdEp' with open('.outPrefix.txt', 'w') as f: f.write(outPrefix) temp = self.whichVol.split(',') if len(temp)==1 and temp[0]=='1': # correct only primary4D volume _eddy_openmp(primaryMaskedVol, primaryBval, primaryBvec, eddy_openmp_params) elif len(temp)==2 and temp[1]=='2': # sylvain would like to correct both primary and secondary volumes with open(indexFile, 'a') as f: for i in range(numVol2): f.write('2\n') # join both bvalFiles bvals1= read_bvals(primaryBval) if dim2==4 and not secondaryBval: bvals2= bvals1.copy() elif dim2==4 and secondaryBval: bvals2= read_bvals(secondaryBval) elif dim2==3: bvals2=[0] combinedBvals = 'combinedBvals.txt' write_bvals(combinedBvals, bvals1+bvals2) # join both bvecFiles bvecs1= read_bvecs(primaryBvec) if dim2==4 and not secondaryBvec: bvecs2= bvecs1.copy() elif dim2==4 and secondaryBvec: bvecs2= read_bvecs(secondaryBvec) elif dim2==3: bvecs2=[[0,0,0]] # join both bvecFiles combinedBvecs = 'combinedBvecs.txt' write_bvecs(combinedBvecs, bvecs1+bvecs2) combinedData= 'combinedData.nii.gz' fslmerge('-t', combinedData, primaryMaskedVol, secondaryMaskedVol) _eddy_openmp(combinedData, combinedBvals, combinedBvecs, eddy_openmp_params) else: raise ValueError('Invalid --whichVol') # rename topupMask to have same prefix as that of eddy corrected volume move(topupMask, outPrefix + '_mask.nii.gz')
def main(self): from plumbum.cmd import eddy_openmp if self.useGpu: try: from plumbum.cmd import nvcc nvcc['--version'] & FG print('\nCUDA found, looking for available GPU\n') from GPUtil import getFirstAvailable getFirstAvailable() print('available GPU found, looking for eddy_cuda executable\n' 'make sure you have created a softlink according to ' 'https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy/UsersGuide') from plumbum.cmd import eddy_cuda as eddy_openmp print('\neddy_cuda executable found\n') except: print( 'nvcc, available GPU, and/or eddy_cuda was not found, using eddy_openmp' ) prefix = self.dwi_file.name.split('.')[0] self.outDir.mkdir() outPrefix = pjoin(self.outDir._path, prefix + '_Ed') if not self.b0_brain_mask: logging.info('Mask not provided, creating mask ...') self.b0_brain_mask = outPrefix + '_mask.nii.gz' bet_mask(self.dwi_file, self.b0_brain_mask, 4, bvalFile=self.bvals_file, BET_THRESHOLD=self.betThreshold) _, _, eddy_openmp_params = obtain_fsl_eddy_params( self.eddy_config_file._path) print('eddy_openmp/cuda parameters') print(eddy_openmp_params) print('') eddy_openmp[f'--imain={self.dwi_file}', f'--mask={self.b0_brain_mask}', f'--acqp={self.acqparams_file}', f'--index={self.index_file}', f'--bvecs={self.bvecs_file}', f'--bvals={self.bvals_file}', f'--out={outPrefix}', eddy_openmp_params.split()] & FG # free space, see https://github.com/pnlbwh/pnlNipype/issues/82 if '--repol' in eddy_openmp_params: rm[f'{outPrefix}.eddy_outlier_free_data.nii.gz'] & FG bvals = np.array(read_bvals(self.bvals_file)) ind = [ i for i in range(len(bvals)) if bvals[i] > B0_THRESHOLD and bvals[i] <= REPOL_BSHELL_GREATER ] if '--repol' in eddy_openmp_params and len(ind): print( '\nDoing eddy_openmp/cuda again without --repol option ' 'to obtain eddy correction w/o outlier replacement for b<=500 shells\n' ) eddy_openmp_params = eddy_openmp_params.split() eddy_openmp_params.remove('--repol') print(eddy_openmp_params) print('') wo_repol_outDir = self.outDir.join('wo_repol') wo_repol_outDir.mkdir() wo_repol_outPrefix = pjoin(wo_repol_outDir, prefix + '_Ed') eddy_openmp[ f'--imain={self.dwi_file}', f'--mask={self.b0_brain_mask}', f'--acqp={self.acqparams_file}', f'--index={self.index_file}', f'--bvecs={self.bvecs_file}', f'--bvals={self.bvals_file}', f'--out={wo_repol_outPrefix}', eddy_openmp_params] & FG repol_bvecs = np.array( read_bvecs(outPrefix + '.eddy_rotated_bvecs')) wo_repol_bvecs = np.array( read_bvecs(wo_repol_outPrefix + '.eddy_rotated_bvecs')) merged_bvecs = repol_bvecs.copy() merged_bvecs[ind, :] = wo_repol_bvecs[ind, :] repol_data = load_nifti(outPrefix + '.nii.gz') wo_repol_data = load_nifti(wo_repol_outPrefix + '.nii.gz') merged_data = repol_data.get_fdata().copy() merged_data[..., ind] = wo_repol_data.get_fdata()[..., ind] save_nifti(outPrefix + '.nii.gz', merged_data, repol_data.affine, hdr=repol_data.header) # copy bval,bvec to have same prefix as that of eddy corrected volume write_bvecs(outPrefix + '.bvec', merged_bvecs) copyfile(self.bvals_file, outPrefix + '.bval') # clean up rm['-r', wo_repol_outDir] & FG else: # copy bval,bvec to have same prefix as that of eddy corrected volume copyfile(outPrefix + '.eddy_rotated_bvecs', outPrefix + '.bvec') copyfile(self.bvals_file, outPrefix + '.bval')
def _eddy_openmp(modData, modBvals, modBvecs, eddy_openmp_params): print('eddy_openmp/cuda parameters') print(eddy_openmp_params) print('') eddy_openmp[f'--imain={modData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={modBvecs}', f'--bvals={modBvals}', f'--out={outPrefix}', f'--topup={topup_results}', eddy_openmp_params.split()] & FG bvals = np.array(read_bvals(modBvals)) ind = [ i for i in range(len(bvals)) if bvals[i] > B0_THRESHOLD and bvals[i] <= REPOL_BSHELL_GREATER ] if '--repol' in eddy_openmp_params and len(ind): print( '\nDoing eddy_openmp/cuda again without --repol option ' 'to obtain eddy correction w/o outlier replacement for b<=500 shells\n' ) eddy_openmp_params = eddy_openmp_params.split() eddy_openmp_params.remove('--repol') print(eddy_openmp_params) print('') wo_repol_outDir = local.path(outPrefix).dirname.join( 'wo_repol') wo_repol_outDir.mkdir() wo_repol_outPrefix = pjoin(wo_repol_outDir, basename(outPrefix)) eddy_openmp[f'--imain={modData}', f'--mask={topupMask}', f'--acqp={self.acqparams_file}', f'--index={indexFile}', f'--bvecs={modBvecs}', f'--bvals={modBvals}', f'--out={wo_repol_outPrefix}', f'--topup={topup_results}', eddy_openmp_params] & FG repol_bvecs = np.array( read_bvecs(outPrefix + '.eddy_rotated_bvecs')) wo_repol_bvecs = np.array( read_bvecs(wo_repol_outPrefix + '.eddy_rotated_bvecs')) merged_bvecs = repol_bvecs.copy() merged_bvecs[ind, :] = wo_repol_bvecs[ind, :] repol_data = load(outPrefix + '.nii.gz') wo_repol_data = load(wo_repol_outPrefix + '.nii.gz') merged_data = repol_data.get_fdata().copy() merged_data[..., ind] = wo_repol_data.get_fdata()[..., ind] save_nifti(outPrefix + '.nii.gz', merged_data, repol_data.affine, hdr=repol_data.header) # copy bval,bvec to have same prefix as that of eddy corrected volume write_bvecs(outPrefix + '.bvec', merged_bvecs) copyfile(modBvals, outPrefix + '.bval') else: # copy bval,bvec to have same prefix as that of eddy corrected volume copyfile(outPrefix + '.eddy_rotated_bvecs', outPrefix + '.bvec') copyfile(modBvals, outPrefix + '.bval')