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Broadband Millimeter-Wave Propagation Measurements and Models Using Adaptive-Beam Antennas for Outdoor Urban Cellular Communications
- T. Rappaport, F. Gutierrez, Eshar Ben-Dor, J. Murdock, Y. Qiao, Jonathan I. Tamir
- BusinessIEEE Transactions on Antennas and Propagation
Measurements and models that may be used to design future fifth-generation millimeter-wave cellular networks are provided and insight into antenna beam steering algorithms for these systems are given.
A 38 GHz cellular outage study for an urban outdoor campus environment
- J. Murdock, Eshar Ben-Dor, Y. Qiao, Jonathan I. Tamir, T. Rappaport
- Computer Science, BusinessIEEE Wireless Communications and Networking…
- 1 April 2012
These measurements demonstrate the viability of directional antennas and site-specific planning for future mm-wave cellular, and show that cell radii of ~200 M will provide a very high probability of coverage in an urban environment.
Robust Compressed Sensing MRI with Deep Generative Priors
- A. Jalal, Marius Arvinte, Giannis Daras, E. Price, A. Dimakis, Jonathan I. Tamir
- Computer ScienceNeurIPS
- 3 August 2021
This paper presents the first successful application of the CSGM framework on clinical MRI data, and trains a generative prior on brain scans from the fastMRI dataset, and shows that posterior sampling via Langevin dynamics achieves high quality reconstructions.
Cellular broadband millimeter wave propagation and angle of arrival for adaptive beam steering systems (invited paper)
- T. Rappaport, Y. Qiao, Jonathan I. Tamir, J. Murdock, Eshar Ben-Dor
- Business, Computer ScienceIEEE Radio and Wireless Symposium
- 3 April 2012
This work provides angle of arrival (AOA) and RF multipath characteristics for highly directional antenna beams that may exploit non-line-of-sight propagation paths for futuristic channels at 38 GHz.
Variable-Density Single-Shot Fast Spin-Echo MRI with Deep Learning Reconstruction by Using Variational Networks.
Compared with the conventional parallel imaging and compressed sensing reconstruction (PICS), the variational network (VN) approach accelerates the reconstruction of variable-density single-shot fast spin-echo sequences and achieves improved overall image quality with higher perceived signal-to-noise ratio and sharpness.
Comprehensive motion‐compensated highly accelerated 4D flow MRI with ferumoxytol enhancement for pediatric congenital heart disease
- J. Cheng, K. Hanneman, S. Vasanawala
- Medicine, EngineeringJournal of magnetic resonance imaging : JMRI
- 1 June 2016
To develop and evaluate motion‐compensation and compressed‐sensing techniques in 4D flow MRI for anatomical assessment in a comprehensive ferumoxytol‐enhanced congenital heart disease (CHD) exam.
T2 shuffling: Sharp, multicontrast, volumetric fast spin‐echo imaging
A new acquisition and reconstruction method called T2 Shuffling is presented for volumetric fast spin‐echo (three‐dimensional [3D] FSE) imaging. T2 Shuffling reduces blurring and recovers many images…
Memory-Efficient Learning for Large-Scale Computational Imaging
- Michael R. Kellman, Kevin Zhang, L. Waller
- Computer Science, PhysicsIEEE Transactions on Computational Imaging
- 11 December 2019
This work proposes a memory-efficient learning procedure that exploits the reversibility of the network's layers to enable physics-based learning for large-scale computational imaging systems.
Fast comprehensive single‐sequence four‐dimensional pediatric knee MRI with T2 shuffling
- S. Bao, Jonathan I. Tamir, S. Vasanawala
- MedicineJournal of magnetic resonance imaging : JMRI
- 1 June 2017
To develop and clinically evaluate a pediatric knee magnetic resonance imaging (MRI) technique based on volumetric fast spin‐echo (3DFSE) and compare its diagnostic performance, image quality, and…