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Neuroimage|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 HaldarMagma (New York, N.Y.)|March 19, 2026
Well-designed k-space coverage is important for good MRI denoisingJiayang Wang, 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 HernandoIEEE Transactions on Medical Imaging|May 3, 2015
A majorize-minimize framework for Rician and non-central chi MR imagesDivya Varadarajan, Justin P HaldarMagnetic Resonance in Medicine|May 9, 2015
P-LORAKS: Low-rank modeling of local k-space neighborhoods with parallel imaging dataJustin P Haldar, Jingwei ZhuoMagnetic Resonance in Medicine|June 3, 2021
Local perturbation responses and checkerboard tests: Characterization tools for nonlinear MRI methodsChin-Cheng Chan, Justin P HaldarNMR in Biomedicine|September 15, 2022
High-fidelity, high-spatial-resolution diffusion magnetic resonance imaging of ex vivo whole human brain at ultra-high gradient strength with structured low-rank echo-planar imaging ghost correctionGabriel Ramos-Llordén, Rodrigo A Lobos, Tae Hyung Kim, et al.Pageof 8