R
Richard Bayford
Researcher at Middlesex University
Publications - 229
Citations - 4803
Richard Bayford is an academic researcher from Middlesex University. The author has contributed to research in topics: Electrical impedance tomography & Electrical impedance. The author has an hindex of 33, co-authored 219 publications receiving 4241 citations. Previous affiliations of Richard Bayford include University College London & University College Hospital.
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Journal ArticleDOI
GREIT: a unified approach to 2D linear EIT reconstruction of lung images.
Andy Adler,John H. Arnold,Richard Bayford,Andrea Borsic,Brian H. Brown,Paul Dixon,Theo J.C. Faes,Inéz Frerichs,Hervé Gagnon,Yvo Garber,Bartłomiej Grychtol,Günter Hahn,William R. B. Lionheart,Anjum Malik,Robert P Patterson,Janet Stocks,Andrew Tizzard,Norbert Weiler,Gerhard K. Wolf +18 more
TL;DR: This paper describes the unified approach to linear image reconstruction developed for GREIT (Graz consensus Reconstruction algorithm for EIT), which represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring.
Journal ArticleDOI
Bioimpedance tomography (electrical impedance tomography)
TL;DR: A review of the development of EIT and its clinical applications, examining hardware for the collection of data and reconstruction algorithms to generate images, and looking at future developments that are evolving from EIT.
Journal ArticleDOI
Three-dimensional electrical impedance tomography of human brain activity.
TL;DR: Electrical Impedance Tomography images were recorded with scalp electrodes and an EIT system, specially optimized for recording brain function, in 39 adult human subjects during visual, somatosensory, or motor activity and demonstrated significant impedance changes in the appropriate cortical region.
Journal ArticleDOI
Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method.
Andrew P. Bagshaw,Adam D. Liston,Richard Bayford,Andrew Tizzard,Adam Gibson,A.Thomas Tidswell,Matthew K Sparkes,Hamid Dehghani,Colin D. Binnie,David Holder +9 more
TL;DR: In this paper, a simplified reconstruction algorithm was used which modelled the head as a homogeneous sphere and incorporated realistic geometry and conductivity distributions using the finite element method, which significantly improved the quality of EIT images.
Journal ArticleDOI
Whither lung EIT: where are we, where do we want to go and what do we need to get there?
Andy Adler,Marcelo B. P. Amato,John H. Arnold,Richard Bayford,Marc Bodenstein,Stephan H. Bohm,Brian H. Brown,Inéz Frerichs,Ola Stenqvist,Norbert Weiler,Gerhard K. Wolf +10 more
TL;DR: It is argued that lung EIT research has arrived at an important transition, and it is now clear that valid and reproducible physiological information is available from EIT lung images, and possible clinical scenarios in which EIT could play an important role are developed.