MagneticResonanceImaging / MagneticResonanceImaging/MRIFieldmaps.jl

Plans

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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 b0scale using new derivations
  • store initial cost and then cost after each update in b0map when in track mode
  • validate gradient / cost consistency using autodiff
  • more in-place operations?
  • factor the b0map code into smaller units
  • ultimately the nonlinear CG with monotone line search could be generalized and useful elsewhere
  • request that lldl support units (unlikely). so perhaps use reinterpret?
  • 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

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. 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

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