A Convergent Generalized Krylov Subspace Method for Compressed Sensing MRI Reconstruction with Gradient-Driven Denoisers.

Hong T, Villa U, Fessler JA

DOI: 10.1109/tci.2026.3655489
Published: 2026
Container: IEEE transactions on computational imaging
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1109/tci.2026.3655489,
  title = {A Convergent Generalized Krylov Subspace Method for Compressed Sensing MRI Reconstruction with Gradient-Driven Denoisers.},
  author = {Hong T and Villa U and Fessler JA},
  year = {2026},
  journal = {IEEE transactions on computational imaging},
  doi = {10.1109/tci.2026.3655489},
  url = {https://doi.org/10.1109/tci.2026.3655489}
}

RIS

TY  - JOUR
TI  - A Convergent Generalized Krylov Subspace Method for Compressed Sensing MRI Reconstruction with Gradient-Driven Denoisers.
AU  - Hong T
AU  - Villa U
AU  - Fessler JA
PY  - 2026
JO  - IEEE transactions on computational imaging
DO  - 10.1109/tci.2026.3655489
UR  - https://doi.org/10.1109/tci.2026.3655489
ER  -

APA

T, H., U, V., & JA, F. (2026). A Convergent Generalized Krylov Subspace Method for Compressed Sensing MRI Reconstruction with Gradient-Driven Denoisers.. IEEE transactions on computational imaging. https://doi.org/10.1109/tci.2026.3655489

Source records

pubmed · retrieved 2026-09-25T23:59:07.657Z
europe-pmc · retrieved 2026-09-25T23:59:07.676Z