Matthew J. Middione, Ph.D.

Affiliations: 
2013 Biomedical Physics University of California, Los Angeles, Los Angeles, CA 
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"Matthew Middione"

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Daniel B. Ennis grad student 2013 UCLA
 (Towards Absolutely Quantitative Phase Contrast Magnetic Resonance Imaging.)
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Publications

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Wang K, Middione MJ, Loening AM, et al. (2025) Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising. Investigative Radiology
Middione MJ, Loecher M, Cao X, et al. (2024) Pre-excitation gradients for eddy current nulled convex optimized diffusion encoding (Pre-ENCODE). Magnetic Resonance in Medicine
Oscanoa JA, Middione MJ, Alkan C, et al. (2023) Deep Learning-Based Reconstruction for Cardiac MRI: A Review. Bioengineering (Basel, Switzerland). 10
Moran CJ, Middione MJ, Mazzoli V, et al. (2022) Multishot Diffusion-Weighted MRI of the Breasts in the Supine vs. Prone Position. Journal of Magnetic Resonance Imaging : Jmri
Oscanoa JA, Middione MJ, Syed AB, et al. (2022) Accelerated two-dimensional phase-contrast for cardiovascular MRI using deep learning-based reconstruction with complex difference estimation. Magnetic Resonance in Medicine
Loecher M, Middione MJ, Ennis DB. (2020) A gradient optimization toolbox for general purpose time-optimal MRI gradient waveform design. Magnetic Resonance in Medicine. 84: 3234-3245
Middione MJ, Loecher M, Moulin K, et al. (2020) Optimization methods for magnetic resonance imaging gradient waveform design. Nmr in Biomedicine. e4308
Jahanian H, Holdsworth S, Christen T, et al. (2018) Advantages of Short Repetition Time Resting-State Functional MRI Enabled by Simultaneous Multi-slice Imaging. Journal of Neuroscience Methods
Callaghan F, Maller JJ, Welton T, et al. (2018) Toward personalised diffusion MRI in psychiatry: improved delineation of fibre bundles with the highest-ever angular resolution in vivo tractography. Translational Psychiatry. 8: 91
Zhu K, Dougherty R, Wu H, et al. (2016) Hybrid-Space SENSE Reconstruction for Simultaneous Multi-Slice MRI. Ieee Transactions On Medical Imaging
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