D
Daniel K. Sodickson
Researcher at New York University
Publications - 267
Citations - 18645
Daniel K. Sodickson is an academic researcher from New York University. The author has contributed to research in topics: Iterative reconstruction & Electromagnetic coil. The author has an hindex of 61, co-authored 258 publications receiving 15371 citations. Previous affiliations of Daniel K. Sodickson include Harvard University & Beth Israel Deaconess Medical Center.
Papers
More filters
Journal ArticleDOI
Accelerated cardiac imaging using the SMASH technique.
TL;DR: The increased imaging speed provided by SMASH was used to obtain images with reduced breathhold duration, enhanced spatial resolution, and increased temporal resolution in healthy volunteers.
Journal ArticleDOI
Noninvasive quantification of intracellular sodium in human brain using ultrahigh-field MRI.
Lazar Fleysher,Lazar Fleysher,Niels Oesingmann,Ryan Brown,Daniel K. Sodickson,Graham C. Wiggins,Matilde Inglese +6 more
TL;DR: The first noninvasive quantitative in vivo measurement of ISC and intracellular sodium volume fraction (ISVF) in healthy human brain is reported, made possible by measuring tissue sodium concentration (TSC) and intrACEllular sodium molar fraction (ISMF) at ultra‐high field MRI.
Journal ArticleDOI
Performance evaluation of a 32-element head array with respect to the ultimate intrinsic SNR.
Riccardo Lattanzi,Aaron K. Grant,Aaron K. Grant,Jonathan R. Polimeni,Jonathan R. Polimeni,Michael A. Ohliger,Graham C. Wiggins,Lawrence L. Wald,Lawrence L. Wald,Daniel K. Sodickson +9 more
TL;DR: A tool for evaluating the absolute performance of RF coil arrays, implemented for a spherical geometry, which remained almost constant for 2‐fold acceleration, but deteriorated at higher acceleration factors, suggesting that larger arrays are needed for effective highly‐accelerated parallel imaging.
Journal ArticleDOI
32-element receiver-coil array for cardiac imaging.
Christopher J. Hardy,Harvey E. Cline,Randy Otto John Giaquinto,Thoralf Niendorf,Aaron K. Grant,Daniel K. Sodickson +5 more
TL;DR: A lightweight 32‐element MRI receiver‐coil array was designed and built for cardiac imaging that yields superior performance relative to an eight‐element cardiac array as well as a 32‐ element whole‐torso array for both traditional nonaccelerated cardiac imaging and 3D parallel imaging with acceleration factors as high as 16.
Proceedings ArticleDOI
GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction
Anuroop Sriram,Jure Zbontar,Tullie Murrell,C. Lawrence Zitnick,Aaron Defazio,Daniel K. Sodickson +5 more
TL;DR: In this article, Zhang et al. proposed GrappaNet, a method to integrate traditional parallel imaging methods into deep neural networks that is able to generate high quality reconstructions even for high acceleration factors.