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Magma (New York, N.Y.)|March 19, 2026
Well-designed k-space coverage is important for good MRI denoisingJiayang Wang, Justin P HaldarMagnetic Resonance in Medicine|April 5, 2024
The "hidden noise" problem in MR image reconstructionJiayang Wang, Di An, Justin P HaldarIEEE Transactions on Signal Processing : a Publication of the IEEE Signal Processing Society|June 29, 2023
On Ambiguity in Linear Inverse Problems: Entrywise Bounds on Nearly Data-Consistent Solutions and Entrywise Condition NumbersJustin P HaldarIEEE Transactions on Medical Imaging|March 6, 2014
Low-rank modeling of local k-space neighborhoods (LORAKS) for constrained MRIJustin P HaldarIEEE Transactions on Medical Imaging|February 5, 2019
OEDIPUS: An Experiment Design Framework for Sparsity-Constrained MRIJustin P Haldar, Daeun KimNeuroimage|August 24, 2017
A theoretical signal processing framework for linear diffusion MRI: Implications for parameter estimation and experiment designDivya Varadarajan, Justin P HaldarSignal Processing|March 15, 2016
Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse RecoveryDaeun Kim, Justin P HaldarProceedings. IEEE International Symposium on Biomedical Imaging|April 9, 2019
TOWARDS OPTIMAL LINEAR ESTIMATION OF ORIENTATION DISTRIBUTION FUNCTIONS WITH ARBITRARILY SAMPLED DIFFUSION MRI DATADivya Varadarajan, Justin P HaldarIEEE Transactions on Computational Imaging|August 30, 2021
PALMNUT: An Enhanced Proximal Alternating Linearized Minimization Algorithm with Application to Separate Regularization of Magnitude and PhaseYunsong Liu, Justin P HaldarIEEE Signal Processing Letters|March 6, 2012
Rank-Constrained Solutions to Linear Matrix Equations Using PowerFactorizationJustin P Haldar, Diego HernandoPageof 17