P
Philip V. Bayly
Researcher at Washington University in St. Louis
Publications - 233
Citations - 9354
Philip V. Bayly is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Magnetic resonance elastography & Shear waves. The author has an hindex of 49, co-authored 216 publications receiving 8159 citations. Previous affiliations of Philip V. Bayly include University of Birmingham & University of Washington.
Papers
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Diffusion tensor imaging reliably detects experimental traumatic axonal injury and indicates approximate time of injury.
TL;DR: Diffusion tensor imaging was more sensitive to injury than conventional magnetic resonance imaging, and relative anisotropy distinguished injured from control mice with no overlap between groups, and changes strongly predicted the approximate time since trauma.
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Stability of Interrupted Cutting by Temporal Finite Element Analysis
TL;DR: In this article, the problem of predicting stability in interrupted cutting is solved by matching the free response with an approximate solution that is valid white the tool is cutting, which can be used to predict stability for arbitrary times in the cut; the current method is applicable only to a single degree of freedom.
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Stability of up-milling and down-milling, part 1: alternative analytical methods
TL;DR: In this paper, the dynamic stability of the milling process is investigated through a single degree of freedom mechanical model and two alternative analytical methods are introduced, both based on finite dimensional discrete map representations of the governing time periodic delay differential equation.
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Detection of traumatic axonal injury with diffusion tensor imaging in a mouse model of traumatic brain injury.
C. L. Mac Donald,Krikor Dikranian,Sheng-Kwei Song,Philip V. Bayly,David M. Holtzman,David L. Brody,David L. Brody +6 more
TL;DR: Diffusion tensor imaging is able to detect axonal injury, and the hypothesis that DTI may be more sensitive than conventional imaging methods for this purpose is supported.
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Estimation of conduction velocity vector fields from epicardial mapping data
Philip V. Bayly,Bruce H. Kenknight,Jack M. Rogers,R.E. Hillsley,Raymond E. Ideker,William M. Smith +5 more
TL;DR: An automated method to estimate vector fields of propagation velocity from observed epicardial extracellular potentials is introduced and is used to characterize propagation qualitatively and quantitatively during both simple and complex rhythms.