aslprep.sdcflows.workflows.phdiff module
Phase-difference B0 estimation.
Phase-difference B0 estimation
The field inhomogeneity inside the scanner (fieldmap) is proportional to the phase drift between two subsequent GRE sequence.
This corresponds to this section of the BIDS specification.
- init_phdiff_wf(omp_nthreads, name='phdiff_wf')[source]
Distortion correction of EPI sequences using phase-difference maps.
Estimates the fieldmap using a phase-difference image and one or more magnitude images corresponding to two or more GRE acquisitions. The most delicate bit of this workflow is the phase-unwrapping process: phase maps are clipped in the range \([0 \dotsb 2\pi )\). To find the integer number of offsets that make a region continously smooth with its neighbour, FSL PRELUDE is run [Jenkinson2003]. FSL PRELUDE takes wrapped maps in the range 0 to 6.28, as per the user guide. For the phase-difference maps, recentering back to \([-\pi \dotsb \pi )\) is necessary. After some massaging and the application of the effective echo spacing parameter, the phase-difference maps can be converted into a B0 field map in Hz units. The original code was taken from nipype.
- Workflow Graph
(Source code, png, svg, pdf)
- Parameters:
omp_nthreads (int) – Maximum number of threads an individual process may use
- Inputs:
magnitude (list of os.pathlike) – List of path(s) the GRE magnitude maps.
phasediff (list of tuple(os.pathlike, dict)) – List containing one GRE phase-difference map with its corresponding metadata (requires
EchoTime1andEchoTime2), or the phase maps for the two subsequent echoes, with their metadata (requiresEchoTime).
- Outputs:
fmap_ref (pathlike) – The average magnitude image, skull-stripped
fmap_mask (pathlike) – The brain mask applied to the fieldmap
fmap (pathlike) – The estimated fieldmap in Hz
References
[Jenkinson2003]Jenkinson, M. (2003) Fast, automated, N-dimensional phase-unwrapping algorithm. MRM 49(1):193-197. doi:10.1002/mrm.10354.
