J
Jason P. Stockmann
Researcher at Harvard University
Publications - 69
Citations - 1782
Jason P. Stockmann is an academic researcher from Harvard University. The author has contributed to research in topics: Electromagnetic coil & Medicine. The author has an hindex of 16, co-authored 54 publications receiving 1091 citations. Previous affiliations of Jason P. Stockmann include California Institute of Technology & Yale University.
Papers
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Journal ArticleDOI
7 Tesla MRI of the ex vivo human brain at 100 micron resolution
Brian L. Edlow,Azma Mareyam,Andreas Horn,Jonathan R. Polimeni,Thomas Witzel,M. Dylan Tisdall,Jean C. Augustinack,Jason P. Stockmann,Bram R. Diamond,Allison Stevens,Lee S. Tirrell,Rebecca D. Folkerth,Lawrence L. Wald,Bruce Fischl,Andre van der Kouwe +14 more
TL;DR: An ultra-high resolution MRI dataset of an ex vivo human brain specimen donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes is presented.
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High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS)
Kawin Setsompop,Qiuyun Fan,Jason P. Stockmann,Berkin Bilgic,Susie Y. Huang,Stephen F. Cauley,Aapo Nummenmaa,Fuyixue Wang,Fuyixue Wang,Yogesh Rathi,Thomas Witzel,Lawrence L. Wald +11 more
TL;DR: To develop an efficient acquisition for high‐resolution diffusion imaging and allow in vivo whole‐brain acquisitions at 600‐ to 700‐μm isotropic resolution.
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Two-dimensional imaging in a lightweight portable MRI scanner without gradient coils.
Clarissa Zimmerman Cooley,Clarissa Zimmerman Cooley,Jason P. Stockmann,Brandon D. Armstrong,Mathieu Sarracanie,Michael H. Lev,Matthew S. Rosen,Lawrence L. Wald,Lawrence L. Wald +8 more
TL;DR: In this paper, the authors proposed a rotating spatial encoding magnetic field (rSEM) to create generalized projections which encode the iteratively reconstructed two-dimensional (2D) image.
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Low‐cost and portable MRI
Lawrence L. Wald,Lawrence L. Wald,Patrick C. McDaniel,Patrick C. McDaniel,Thomas Witzel,Jason P. Stockmann,Clarissa Zimmerman Cooley +6 more
TL;DR: This review examines the technical forces and trade-offs that might facilitate a large step forward in the push to "jail-break" MRI from its centralized location in healthcare and allow it to reach larger patient populations and achieve new uses.
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O-space imaging: Highly efficient parallel imaging using second-order nonlinear fields as encoding gradients with no phase encoding.
TL;DR: The theory is presented, an algorithm is introduced for image reconstruction, and simulations reveal that O‐space encoding achieves high encoding efficiency compared to sensitivity encoding (SENSE) radial k‐space trajectories, and parallel imaging technique with localized gradients (PatLoc), suggesting that O-space imaging holds great potential for accelerated scanning.