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Paul Morris

Researcher at University of Sheffield

Publications -  283
Citations -  12193

Paul Morris is an academic researcher from University of Sheffield. The author has contributed to research in topics: Fractional flow reserve & Medicine. The author has an hindex of 49, co-authored 252 publications receiving 10739 citations. Previous affiliations of Paul Morris include Johns Hopkins University & Center for Complex Systems and Brain Sciences.

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Book ChapterDOI

Reconstruction of coronary trees from 3DRA using a 3D+t statistical cardiac prior.

TL;DR: This paper proposes a method for finding 3D+T points on coronary artery tree given tracked 2D+t point locations in X-ray rotational angiography images using a bilinear model of ventricle as a spatio-temporal constraint on the nonrigid structure of the coronary artery.

Discovery of Regulatory Elements in Oomycete Orthologs.

TL;DR: Putative regulatory elements and putative coacting regulatory element clusters (transcription factor binding modules) for the ABC transporter family and the sulfate assimilation pathway are discovered.
Journal ArticleDOI

The Impact of Virtual Fractional Flow Reserve and Virtual Coronary Intervention on Treatment Decisions in the Cardiac Catheter Laboratory.

TL;DR: In this article, the authors investigated the effect of adding fractional flow reserve (FFR) and virtual coronary intervention (VCI) to angiography in patient assessment and management and found that disclosure of FFR and VCI resulted in an increase in operator confidence in their decision.
Journal ArticleDOI

Computing Fractional Flow Reserve From Invasive Coronary Angiography: Getting Closer.

TL;DR: FFR use remains trapped within the world of PTCA guidance, as originally outlined by Pijls et al, because the weight of evidence supporting FFR is in the context of chronic stable coronary disease, whereas the workload of the interventionist is increasingly made up of acute or unstable disease.
Proceedings Article

Bounding the resource availability of activities with linear resource impact

TL;DR: This work shows how to construct tight bounds for resource availability as a function of time in LRTNs; for a broad class of problems, the complexity is polynomial time in the time horizon h and the number of activities n.