NexOP jointly optimizes NEX-aware k-space sampling probabilities and multi-measurement reconstruction to raise effective SNR in low-field MRI under a fixed total sampling budget.
citation dossier
Revisitingℓ1-wavelet compressed-sensing mri in the era of deep learn- ing.Proceedings of the National Academy of Sciences, 119(33)
1Pith papers citing it
1reference links
eess.IVtop field · 1 papers
UNVERDICTEDtop verdict bucket · 1 papers
why this work matters in Pith
Pith has found this work in 1 reviewed paper. Its strongest current cluster is eess.IV (1 papers). The largest review-status bucket among citing papers is UNVERDICTED (1 papers). For highly cited works, this page shows a dossier first and a bounded explorer second; it never tries to render every citing paper at once.
fields
eess.IV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
NexOP: Joint Optimization of NEX-Aware k-space Sampling and Image Reconstruction for Low-Field MRI
NexOP jointly optimizes NEX-aware k-space sampling probabilities and multi-measurement reconstruction to raise effective SNR in low-field MRI under a fixed total sampling budget.