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Merging Cartesian and non-Cartesian sampling through GoLF-SPARKLING

August 2024 Chaithya Giliyar Radhakrishna, Guillaume Daval-Frérot, Aurélien Massire, et al. ISMRM & ISMRT Annual Meeting & Exhibition · Conference abstract
#SPARKLING #Non-Cartesian Sampling #k-space Sampling #non-Cartesian sampling #k-space trajectory #golf

Abstract

Cartesian sampling can acquire a given k-space region with minimum redundancy, while non-Cartesian sampling can help achieve a larger k-space coverage. Through generalized affine constraints in SPARKLING and an adapted target sampling density, for the first time non-Cartesian and Cartesian sampling are merged within same trajectory, giving the best of both worlds. With Gridding of Low Frequencies (GoLF), we get SPARKLING k-space trajectories which carry out Cartesian sampling at the center of k-space. This approach paves the way for designing new kind of compound sampling patterns, which enforces Cartesian and non-Cartesian sampling within the same trajectory.

Details

  • Type of work: Conference abstract
  • Venue: ISMRM & ISMRT Annual Meeting & Exhibition
  • Published: 14 August 2024
  • DOI: 10.58530/2023/2222
  • Authors: Chaithya Giliyar Radhakrishna, Guillaume Daval-Frérot, Aurélien Massire, Alexandre Vignaud, and Philippe Ciuciu
  • Data sources: ref.bib, OpenAlex

BibTeX

@article{chaithyamerging,
  title={Merging Cartesian and non-Cartesian sampling through GoLF-SPARKLING},
  author={Chaithya, GR and Daval-Fr{\'e}rot, Guillaume and Massire, Aur{\'e}lien and Vignaud, Alexandre and Ciuciu, Philippe}
}