New masking for T1 and DWI, new registration technique for DWI->T1 tr…

…ansform (#40)

* New masking strategy for preproc
* Changed connectivity in clean_mask
* Edited slurm command for better lemaitre4 HCP cluster compatibility
* Improved T1 mask for synb0disco
* Added transform from DWI2T1 using fsl epi_reg
* Improved T1 mask with mri_synth_strip

elikopy/core.py

@@ -459,7 +459,7 @@ def patient_list(self, folder_path=None, bids_path=None, reverseEncoding=True):
         f.write("["+log_prefix+"] " + datetime.datetime.now().strftime("%d.%b %Y %H:%M:%S") + ": Patient list generated\n")
         f.close()
 
-    def preproc(self, folder_path=None, reslice=False, reslice_addSlice=False, denoising=False, denoising_algorithm="mppca_mrtrix", gibbs=False, topup=False, topupConfig=None, forceSynb0DisCo=False, useGPUsynb0DisCo=False, eddy=False, biasfield=False, biasfield_bsplineFitting=[100,3], biasfield_convergence=[1000,0.001], patient_list_m=None, starting_state=None, bet_median_radius=2, bet_numpass=1, bet_dilate=2, static_files_path=None, cuda=None, cuda_name="eddy_cuda10.1", s2v=[0,5,1,'trilinear'], olrep=[False, 4, 250, 'sw'], eddy_additional_arg="", slurm=None, slurm_email=None, slurm_timeout=None, cpus=None, slurm_mem=None, qc_reg=True, niter=5, slspec_gc_path=None, report=True):
+    def preproc(self, folder_path=None, reslice=False, reslice_addSlice=False, denoising=False, gibbs=False, topup=False, topupConfig=None, forceSynb0DisCo=False, useGPUsynb0DisCo=False, eddy=False, biasfield=False, biasfield_bsplineFitting=[100,3], biasfield_convergence=[1000,0.001], patient_list_m=None, starting_state=None, bet_median_radius=2, bet_numpass=1, bet_dilate=2, static_files_path=None, cuda=None, cuda_name="eddy_cuda10.1", s2v=[0,5,1,'trilinear'], olrep=[False, 4, 250, 'sw'], eddy_additional_arg="", slurm=None, slurm_email=None, slurm_timeout=None, cpus=None, slurm_mem=None, qc_reg=True, niter=5, slspec_gc_path=None, report=True):
         """ Performs data preprocessing. By default only the brain extraction is enabled. Optional preprocessing steps include : reslicing,
         denoising, gibbs ringing correction, susceptibility field estimation, EC-induced distortions and motion correction, bias field correction.
         The results are stored in the preprocessing subfolder of each study subject <folder_path>/subjects/<subjects_ID>/dMRI/preproc.
@@ -499,8 +499,6 @@ def preproc(self, folder_path=None, reslice=False, reslice_addSlice=False, denoi
         """
 
         assert starting_state in (None, "denoising", "gibbs", "topup", "eddy", "biasfield", "report", "post_report", "topup_synb0DisCo_Registration", "topup_synb0DisCo_Inference", "topup_synb0DisCo_Apply", "topup_synb0DisCo_topup"), 'invalid starting state!'
-        if denoising==True:
-            assert denoising_algorithm in ["patch2self", "mppca_mrtrix", "mppca_dipy"], 'invalid denoising algorithm!'
         if starting_state=="denoising":
             assert denoising == True, 'if starting_state is denoising, denoising must be True!'
         if starting_state=="gibbs":
@@ -548,7 +546,7 @@ def preproc(self, folder_path=None, reslice=False, reslice_addSlice=False, denoi
                     p_job = {
                         "wrap": "export OMP_NUM_THREADS="+str(tot_cpu)+" ; export FSLPARALLEL="+str(tot_cpu)+" ; python -c 'from elikopy.individual_subject_processing import preproc_solo; preproc_solo(\"" + folder_path + "/\",\"" + p + "\",eddy=" + str(
                             eddy) + ",biasfield=" + str(biasfield)  + ",biasfield_convergence=[" + str(biasfield_convergence[0]) + "," + str(biasfield_convergence[1]) + "],biasfield_bsplineFitting=[" + str(biasfield_bsplineFitting[0]) + "," + str(biasfield_bsplineFitting[1]) + "],denoising=" + str(
-                            denoising) + ",denoising_algorithm=\"" + str(denoising_algorithm) +"\",reslice=" + str(reslice) + ",reslice_addSlice=" + str(reslice_addSlice) + ",gibbs=" + str(
+                            denoising) + ",reslice=" + str(reslice) + ",reslice_addSlice=" + str(reslice_addSlice) + ",gibbs=" + str(
                             gibbs) + ",topup=" + str(topup) + ",forceSynb0DisCo=" + str(forceSynb0DisCo) + ",useGPUsynb0DisCo=" + str(useGPUsynb0DisCo) + ",topupConfig=\"" + str(topupConfig) + "\",starting_state=\"" + str(starting_state) + "\",static_files_path=\""+ static_files_path +"\" ,bet_median_radius=" + str(
                             bet_median_radius) + ",bet_dilate=" + str(bet_dilate) + ", qc_reg=" + str(qc_reg) + ", report=" + str(report) + ", slspec_gc_path=" + str(slspec_gc_path) + ", core_count=" + str(core_count)+ ", niter=" + str(niter)+",bet_numpass=" + str(
                             bet_numpass) + ",cuda=" + str(cuda) + ",cuda_name=\"" + str(cuda_name) + "\",s2v=[" + str(s2v[0]) + "," + str(s2v[1]) + "," + str(s2v[2]) + ",\"" + str(s2v[3]) + "\"],olrep=[" + str(olrep[0]) + "," + str(olrep[1]) + "," + str(olrep[2]) + ",\"" + str(olrep[3]) + "\"], " + "eddy_additional_arg=\"" + str(eddy_additional_arg) + "\" )'",
@@ -595,7 +593,7 @@ def preproc(self, folder_path=None, reslice=False, reslice_addSlice=False, denoi
                     f.write("["+log_prefix+"] " + datetime.datetime.now().strftime("%d.%b %Y %H:%M:%S") + ": Successfully submited job %s using slurm\n" % p_job_id)
                 else:
                     core_count = 1 if cpus is None else cpus
-                    preproc_solo(folder_path + "/",p,reslice=reslice,reslice_addSlice=reslice_addSlice,denoising=denoising, denoising_algorithm=denoising_algorithm, gibbs=gibbs,
+                    preproc_solo(folder_path + "/",p,reslice=reslice,reslice_addSlice=reslice_addSlice,denoising=denoising, gibbs=gibbs,
                                  topup=topup, topupConfig=topupConfig, forceSynb0DisCo=forceSynb0DisCo, useGPUsynb0DisCo=useGPUsynb0DisCo,
                                  eddy=eddy,biasfield=biasfield, biasfield_bsplineFitting=biasfield_bsplineFitting, biasfield_convergence=biasfield_convergence,
                                  starting_state=starting_state,