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PyGROG

  • PyGROG

User Guides

  • Getting Started
    • Getting Started
    • Installation
  • Installation

Examples

  • Examples
    • Basic Usage: mri-nufft Baseline vs PyGROG
    • Batched and Stacked Reconstructions with PyGROG
    • Gadgets with mri-nufft Data: Subspace and B0 ORC
    • Utils Tour: Coil Compression and NLINV
    • Iterative Solve: CG, LSMR, and Polynomial Preconditioning
    • Toeplitz-Embedded Self-Adjoint A^H A for SparseFFT Gadgets
    • End-to-end CS reconstruction with sigpy, deepinv and mrpro

API Reference

  • API Reference
    • Calibration
      • coil_compression
      • nlinv
    • GROG
      • GrogInterpolator
    • Gadgets
      • OffResonanceGadget
      • SubspaceGadget
      • with_offresonance
      • with_subspace
    • Operators
      • SparseFFT
      • MaskedFFT
    • Interoperability
      • GrogLinop
      • GrogLinearOp
      • GrogLinearPhysics

Explanations

  • Explanations
    • The GRAPPA Algorithm
    • GROG: GRAPPA Operator Gridding
    • Model Extensions

Miscellaneous

  • Contributors
  • Code of Conduct
  • License
  • Developing PyGROG

Related Projects

  • mri-nufft
  • mrpro
  • sigpy
  • deepinverse
  • Repository
  • Suggest edit
  • Open issue
  • .rst

Explanations

Explanations#

  • The GRAPPA Algorithm
    • Background: Parallel Imaging in MRI
    • The GRAPPA Linear Prediction Model
    • Practical Considerations
    • References
  • GROG: GRAPPA Operator Gridding
    • From Cartesian GRAPPA to Non-Cartesian Gridding
    • Algorithm Outline
    • Complexity and Accuracy
    • Comparison with the NUFFT
    • References
  • Model Extensions
    • Parallel Imaging (Multi-Coil)
    • Low-Rank Temporal Subspace
    • Off-Resonance Correction
    • References

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GrogLinearPhysics

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The GRAPPA Algorithm

By PyGROG contributors

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