Hey guys-
I have been trying to perform some analysis collected on patients after deep brain stimulator (DBS) placement. We collect data on a Philips Intera 1.5T. There is a “stock” field map sequence that collects gradient reversal data and outputs two EPI volumes - one with AP and one with PA collection. I then collect a resting state sequence (in AP) as well. When I process the data with afni_proc.py the results are not terrible. I used ANATICOR instead of WM or CSF regressors. The DBS metal artifact seems tolerable. Nevertheless, I would like to use unWarpEPI.py to correct any susceptibility artifact. The output is more distorted than the original EPI. Here are the calls that I am using to process my data:
unWarpEPI.py -f EPI_PA_field.nii -r EPI_AP_field.nii -d EPI_resting
-a T1_mprage.nii --giant_move
afni_proc.py -subj_id ${PTDIR}
-dsets ${DATADIR}/EPI_resting.nii
-copy_anat ${DATADIR}/T1_mprage.nii
-scr_overwrite
-blocks despike tshift align tlrc volreg blur mask regress
-tcat_remove_first_trs 0
-volreg_align_to MIN_OUTLIER
-volreg_align_e2a –tlrc_NL_warp
-volreg_tlrc_warp
-align_opts_aea -cost lpc+ZZ -giant_move
-mask_apply epi
-blur_size 6.0
-regress_anaticor_fast
-regress_censor_motion 0.4
-regress_bandpass 0.01 0.1
-regress_apply_mot_types demean deriv
-regress_run_clustsim no
-regress_est_blur_errts
Thoughts?