Estimating the susceptibility distortions without fieldmaps.
Fieldmap-less estimation (experimental)¶
In the absence of direct measurements of fieldmap data, we provide an (experimental)
option to estimate the susceptibility distortion based on the ANTs symmetric
normalization (SyN) technique.
This feature may be enabled, using the
--use-syn-sdc flag, and will only be
applied if fieldmaps are unavailable.
During the evaluation phase, the
--force-syn flag will cause this estimation to
be performed in addition to fieldmap-based estimation, to permit the direct
comparison of the results of each technique.
Note that, even if
--force-syn is given, the functional outputs of FMRIPREP will
be corrected using the fieldmap-based estimates.
Feedback will be enthusiastically received.
init_syn_sdc_wf(omp_nthreads, epi_pe=None, atlas_threshold=3, name='syn_sdc_wf')¶
Build the fieldmap-less susceptibility-distortion estimation workflow.
This workflow takes a skull-stripped T1w image and reference BOLD image and estimates a susceptibility distortion correction warp, using ANTs symmetric normalization (SyN) and the average fieldmap atlas described in [Treiber2016].
SyN deformation is restricted to the phase-encoding (PE) direction. If no PE direction is specified, anterior-posterior PE is assumed.
SyN deformation is also restricted to regions that are expected to have a >3mm (approximately 1 voxel) warp, based on the fieldmap atlas.
in_reference – reference image
in_reference_brain – skull-stripped reference image
t1w_brain – skull-stripped, bias-corrected structural image
std2anat_xfm – inverse registration transform of T1w image to MNI template
out_reference – the
in_referenceimage after unwarping
out_reference_brain – the
in_reference_brainimage after unwarping
out_warp – the corresponding DFM compatible with ANTs
out_mask – mask of the unwarped input file
Treiber, J. M. et al. (2016) Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images, PLoS ONE 11(3): e0152472. doi:10.1371/journal.pone.0152472.
Wang S, et al. (2017) Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI. Front. Neuroinform. 11:17. doi:10.3389/fninf.2017.00017.
Huntenburg, J. M. (2014) Evaluating Nonlinear Coregistration of BOLD EPI and T1w Images. Berlin: Master Thesis, Freie Universität. PDF.