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Scott H. Robertson

Researcher at Duke University

Publications -  26
Citations -  1162

Scott H. Robertson is an academic researcher from Duke University. The author has contributed to research in topics: Ventilation (architecture) & Imaging phantom. The author has an hindex of 15, co-authored 24 publications receiving 863 citations. Previous affiliations of Scott H. Robertson include GE Healthcare & University of Washington.

Papers
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Journal ArticleDOI

The Belle II Physics Book

E. Kou, +561 more
TL;DR: The Belle II detector as mentioned in this paper is a state-of-the-art detector for heavy flavor physics, quarkonium and exotic states, searches for dark sectors, and many other areas.
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The Belle II Physics Book

E. Kou, +526 more
TL;DR: The physics program of the Belle II experiment, located on the intensity frontier SuperKEKB $e+e^-$ collider, is presented in this article, which includes a wide scope of physics topics: B physics, charm, tau, quarkonium, electroweak precision measurements and dark sector searches.
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Using hyperpolarized 129Xe MRI to quantify regional gas transfer in idiopathic pulmonary fibrosis.

TL;DR: Hyperpolarized 129Xe MRI is a rapid and well-tolerated exam that provides region-specific quantification of interstitial barrier thickness and RBC transfer efficiency and could become a robust tool for measuring disease progression and therapeutic response in patients with IPF, sensitively and non-invasively.
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Single-breath clinical imaging of hyperpolarized (129)Xe in the airspaces, barrier, and red blood cells using an interleaved 3D radial 1-point Dixon acquisition.

TL;DR: A clinically feasible 1‐point Dixon, three‐dimensional radial acquisition strategy to create isotropic 3D MR images of 129Xe in the airspaces, barrier, and red blood cells (RBCs) in a single breath is developed and tested.
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Extending Semiautomatic Ventilation Defect Analysis for Hyperpolarized 129Xe Ventilation MRI

TL;DR: Corrected linear-binning provides a robust means to quantify ventilation images yielding VDP values that are indistinguishable from expert reader scores, while exploiting the entire dynamic range to depict multiple image clusters.