MagneticResonanceImaging / MagneticResonanceImaging/MRIFieldmaps.jl
Plans
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 13
- Forks
- 2
- PR merge metrics
- No merged PRs in 30d
Description
The initial commit is designed mostly to reproduce the results in Julia from https://github.com/ClaireYLin/regularized-field-map-estimation
Planned improvements:
- refine data (or weight) scaling in
b0scaleusing new derivations - store initial cost and then cost after each update in
b0mapwhen intrackmode - validate gradient / cost consistency using autodiff
- more in-place operations?
- factor the
b0mapcode into smaller units - ultimately the nonlinear CG with monotone line search could be generalized and useful elsewhere
- request that
lldlsupport units (unlikely). so perhaps usereinterpret? - timing test for whole-brain 2mm isotropic, e.g., 112 x 112 x 72
- https://github.com/korbinian90/ROMEO.jl for unwrapping
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the initial commit and inspect b0scale, b0map, and lldl; the issue lists these entry points but does not select a single task. Before coding, choose one improvement and define its validation, such as gradient/cost consistency or whole-brain timing, because the current issue has no concrete done criterion.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100