Magnetic resonance fingerprinting

Compressed sensing

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Compressed sensing

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Eigenfaces for Recognition

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Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

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Robust Face Recognition via Sparse Representation

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A concordance correlation coefficient to evaluate reproducibility.

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Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?

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Sparse MRI: The application of compressed sensing for rapid MR imaging

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Generalized autocalibrating partially parallel acquisitions (GRAPPA)

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Face recognition using eigenfaces

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Spin Echoes

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CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

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The Split Bregman Method for L1-Regularized Problems

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An image synthesizer

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Nonuniform fast fourier transforms using min-max interpolation

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Iteratively reweighted algorithms for compressive sensing

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In vivo measurement of T 2 distributions and water contents in normal human brain

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Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state

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Principles and applications of balanced SSFP techniques

Scheffler, K., & Lehnhardt, S. (2003) · European Radiology · doi:10.1007/s00330-003-1957-x · Cited by 714 · see citing works

Magnetic Resonance Imaging

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Rapid magnetic resonance quantification on the brain: Optimization for clinical usage

Warntjes, J. B. M., Leinhard, O. D., West, J., & Lundberg, P. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21635 · Cited by 502 · see citing works

High‐resolution T1 and T2 mapping of the brain in a clinically acceptable time with DESPOT1 and DESPOT2

Deoni, S., Peters, T. M., & Rutt, B. K. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20314 · Cited by 482 · see citing works

MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout

Jiang, Y., Ma, D., Seiberlich, N., Gulani, V., & Griswold, M. A. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25559 · Cited by 422 · see citing works

Practical T2 quantitation for clinical applications

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T1 and T2 in the Brain of Healthy Subjects, Patients with Parkinson Disease, and Patients with Multiple System Atrophy: Relation to Iron Content

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Compressed sensing reconstruction for magnetic resonance parameter mapping

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Compressed-Sensing MRI With Random Encoding

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Time‐resolved contrast‐enhanced imaging with isotropic resolution and broad coverage using an undersampled 3D projection trajectory

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Inversion recovery TrueFISP: Quantification of T 1 , T 2 , and spin density

Schmitt, P., Griswold, M. A., Jakob, P. M., Kotas, M., Gulani, V., Flentje, M. P., & Haase, A. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20058 · Cited by 242 · see citing works

In Vivo Evaluation of Brain Iron in Alzheimer Disease Using Magnetic Resonance Imaging

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Novel method for rapid, simultaneous T 1 , T * 2 , and proton density quantification

Warntjes, J. B. M., Dahlqvist, O. L., & Lundberg, P. (2007) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21165 · Cited by 219 · see citing works

A comparison of one‐shot and recovery methods in T1 imaging

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Water diffusion, T2, and compartmentation in frog sciatic nerve

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Assessment of demyelination, edema, and gliosis by in vivo determination of T1 and T2 in the brain of patients with acute attack of multiple sclerosis

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Magnetic resonance with stochastic excitation

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Multi‐contrast reconstruction with Bayesian compressed sensing

Bilgiç, B., Goyal, V. K., & Adalsteinsson, E. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22956 · Cited by 146 · see citing works

Prospective multiaxial motion correction for fMRI

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Improved radial GRAPPA calibration for real‐time free‐breathing cardiac imaging

Seiberlich, N., Ehses, P., Duerk, J. L., Gilkeson, R., & Griswold, M. A. (2010) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22618 · Cited by 105 · see citing works

IR TrueFISP with a golden‐ratio‐based radial readout: Fast quantification of T 1 , T 2 , and proton density

Ehses, P., Seiberlich, N., Ma, D., Breuer, F., Jakob, P. M., Griswold, M. A., & Gulani, V. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24225 · Cited by 103 · see citing works

Reduction of transient signal oscillations in true‐FISP using a linear flip angle series magnetization preparation

Deshpande, V. S., Chung, Y., Zhang, Q., Shea, S. M., & Li, D. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10337 · Cited by 101 · see citing works

Fast 3D imaging using variable‐density spiral trajectories with applications to limb perfusion

Lee, J. H., Hargreaves, B. A., Hu, B. S., & Nishimura, D. G. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10644 · Cited by 100 · see citing works

Direct parallel image reconstructions for spiral trajectories using GRAPPA

Heidemann, R. M., Griswold, M. A., Seiberlich, N., Krüger, G., Kannengießer, S., Kiefer, B., Wiggins, G. C., Wald, L. L., & Jakob, P. M. (2006) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20951 · Cited by 95 · see citing works

Frontal, temporal, and striatal proton relaxation times in schizophrenic patients and normal comparison subjects

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Severity of hippocampal atrophy correlates with the prolongation of MRI T sub 2 relaxation time in temporal lobe epilepsy but not in Alzheimer's disease

Pitkänen, A., Laakso, M. P., Kälviäinen, R. K., Partanen, K. P. L., Vainio, P. A., Lehtovirta, M., Riekkinen, P. J., & Soininen, H. S. (1996) · Neurology · doi:10.1212/wnl.46.6.1724 · Cited by 73 · see citing works

Time‐optimal multidimensional gradient waveform design for rapid imaging

Hargreaves, B. A., Nishimura, D. G., & Conolly, S. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10666 · Cited by 69 · see citing works

Wideband SSFP: Alternating repetition time balanced steady state free precession with increased band spacing

Nayak, K. S., Lee, H., Hargreaves, B. A., & Hu, B. S. (2007) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21296 · Cited by 67 · see citing works

Frequency resolved single‐shot MR imaging using stochastic k ‐space trajectories

Scheffler, K., & Hennig, J. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910350417 · Cited by 59 · see citing works

Nonuniform Phase-Encode Distributions for MRI Scan Time Reduction

Marseille, G. J., de Beer, R., Fuderer, M., Mehlkopf, A. F., & ORMONDT, D. V. (1996) · Journal of Magnetic Resonance Series B · doi:10.1006/jmrb.1996.0061 · Cited by 54 · see citing works

A simple geometrical description of the TrueFISP ideal transient and steady‐state signal

Schmitt, P., Griswold, M. A., Gulani, V., Haase, A., Flentje, M. P., & Jakob, P. M. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20738 · Cited by 41 · see citing works

Multiple repetition time balanced steady‐state free precession imaging

Çukur, T., & Nishimura, D. G. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21990 · Cited by 30 · see citing works

Robustness of Quantitative Compressive Sensing MRI: The Effect of Random Undersampling Patterns on Derived Parameters for DCE- and DSC-MRI

Smith, D. S., Li, X., Gambrell, J. V., Arlinghaus, L. R., Quarles, C. C., Yankeelov, T. E., & Welch, E. B. (2011) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2011.2172216 · Cited by 29 · see citing works

Use of simulated annealing for the design of multiple repetition time balanced steady‐state free precession imaging

Lee, K. J., Lee, H., Hennig, J., & Leupold, J. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23221 · Cited by 7 · see citing works

An overview of deep learning in medical imaging focusing on MRI

Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058 · see citing works

An overview of deep learning in medical imaging focusing on MRI

Lundervold, A. S., & Lundervold, A. (2018) · NORA - Norwegian Open Research Archives · Cited by 1,012 · see citing works

AI applications to medical images: From machine learning to deep learning

Castiglioni, I., Rundo, L., Codari, M., Leo, G. D., Salvatore, C., Interlenghi, M., Gallivanone, F., Cozzi, A., D’Amico, N. C., & Sardanelli, F. (2021) · Physica Medica · doi:10.1016/j.ejmp.2021.02.006 · Cited by 737 · see citing works

A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology

Iglesias, J. E., Insausti, R., Lerma‐Usabiaga, G., Bocchetta, M., Leemput, K. V., Greve, D. N., van der Kouwe, A. J. W., Fischl, B. R., Caballero‐Gaudes, C., & Paz‐Alonso, P. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.012 · Cited by 558 · see citing works

Pros and cons of ultra-high-field MRI/MRS for human application

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Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation

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Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

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MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout

Jiang, Y., Ma, D., Seiberlich, N., Gulani, V., & Griswold, M. A. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25559 · Cited by 422 · see citing works

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials

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Low‐field MRI: An MR physics perspective

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On modeling

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Molecular imaging in oncology: Current impact and future directions

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SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain

McGivney, D., Pierre, E. Y., Ma, D., Jiang, Y., Saybasili, H., Gulani, V., & Griswold, M. A. (2014) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2337321 · Cited by 308 · see citing works

MR fingerprinting Deep RecOnstruction NEtwork (DRONE)

Cohen, O., Zhu, B., & Rosen, M. S. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27198 · Cited by 313 · see citing works

Compressed sensing for body MRI

Feng, L., Benkert, T., Block, K. T., Sodickson, D. K., Otazo, R., & Chandarana, H. (2016) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25547 · Cited by 306 · see citing works

Quantitative magnetic resonance imaging of brain anatomy and in vivo histology

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Low-Cost High-Performance MRI

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Progressive multiple sclerosis: prospects for disease therapy, repair, and restoration of function

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Molecular Magnetic Resonance Imaging with Gd(III)-Based Contrast Agents: Challenges and Key Advances

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What are normal relaxation times of tissues at 3 T?

Bojorquez, J. Z., Bricq, S., Acquitter, C., Brunotte, F., Walker, P. M., & Lalande, A. (2017) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2016.08.021 · Cited by 286 · see citing works

Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging

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Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

Ahmedt‐Aristizabal, D., Armin, M. A., Denman, S., Fookes, C., & Petersson, L. (2021) · Sensors · doi:10.3390/s21144758 · Cited by 287 · see citing works

Psychoradiology: The Frontier of Neuroimaging in Psychiatry

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A low-cost and shielding-free ultra-low-field brain MRI scanner

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MR fingerprinting for rapid quantification of myocardial T1, T2, and proton spin density

Hamilton, J., Jiang, Y., Chen, Y., Ma, D., Lo, W., Griswold, M. A., & Seiberlich, N. (2016) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26216 · Cited by 246 · see citing works

Accessible magnetic resonance imaging: A review

Geethanath, S., & Vaughan, J. T. (2019) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26638 · Cited by 245 · see citing works

SyMRI of the Brain

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Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction

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Quantifying the Microvascular Origin of BOLD-fMRI from First Principles with Two-Photon Microscopy and an Oxygen-Sensitive Nanoprobe

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Enhancement of Magnetic Resonance Imaging with Metasurfaces

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Rapid and accurate T2 mapping from multi–spin‐echo data using Bloch‐simulation‐based reconstruction

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MR Fingerprinting for Rapid Quantitative Abdominal Imaging

Chen, Y., Jiang, Y., Pahwa, S. S., Ma, D., Lŭ, L., Twieg, M. D., Wright, K. L., Seiberlich, N., Griswold, M. A., & Gulani, V. (2016) · Radiology · doi:10.1148/radiol.2016152037 · Cited by 211 · see citing works

In Vivo Imaging of Human Neuroinflammation

Albrecht, D., Granziera, C., Hooker, J. M., & Loggia, M. L. (2016) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.6b00056 · Cited by 207 · see citing works

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting

Assländer, J., Cloos, M. A., Knöll, F., Sodickson, D. K., Hennig, J., & Lattanzi, R. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26639 · Cited by 207 · see citing works

MR guidance in radiotherapy

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T 2 shuffling: Sharp, multicontrast, volumetric fast spin‐echo imaging

Tamir, J. I., Uecker, M., Chen, W., Lai, P., Alley, M. T., Vasanawala, S. S., & Lustig, M. S. (2016) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26102 · Cited by 196 · see citing works

General overview on the merits of multimodal neuroimaging data fusion

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Targeted nanotechnology for cancer imaging

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Cardiac MRI: State of the Art

Rajiah, P. S., François, C. J., & Leiner, T. (2023) · Radiology · doi:10.1148/radiol.223008 · Cited by 189 · see citing works

Accelerated MR parameter mapping with low‐rank and sparsity constraints

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Optimization Methods for Magnetic Resonance Image Reconstruction: Key Models and Optimization Algorithms

Fessler, J. A. (2020) · IEEE Signal Processing Magazine · doi:10.1109/msp.2019.2943645 · Cited by 188 · see citing works

Microstructural imaging of the human brain with a ‘super-scanner’: 10 key advantages of ultra-strong gradients for diffusion MRI

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Variability and Standardization of Quantitative Imaging

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Large arteriolar component of oxygen delivery implies a safe margin of oxygen supply to cerebral tissue

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Multiparametric imaging with heterogeneous radiofrequency fields

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Magnetic resonance fingerprinting – An overview

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STATEMENT Magnetic Resonance Fingerprinting- a promising new approach

(2015)

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