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Simon R. Arridge
Researcher at University College London
Publications - 602
Citations - 33776
Simon R. Arridge is an academic researcher from University College London. The author has contributed to research in topics: Iterative reconstruction & Optical tomography. The author has an hindex of 83, co-authored 582 publications receiving 30962 citations. Previous affiliations of Simon R. Arridge include University of Cambridge & University College London Hospitals NHS Foundation Trust.
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Proceedings ArticleDOI
Image reconstruction in quantitative photoacoustic tomography using adaptive optical Monte Carlo
TL;DR: In this paper , the authors used the Monte Carlo (MC) method for light transport in the image reconstruction of quantitative photoacoustic tomography (QPAT), where the number of simulated photon packets is adjusted during an iterative image reconstruction.
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Stochastic EM methods with Variance Reduction for Penalised PET Reconstructions
TL;DR: In this paper, a stochastic variance reduced expectation maximization (EM) algorithm is proposed for image reconstruction in positron emission tomography (PET) images, which is based on variance reduction for penalised PET reconstructions.
Proceedings ArticleDOI
Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes
Giulia Maffeis,Antonio Pifferi,Alberto Dalla Mora,Laura Di Sieno,Rinaldo Cubeddu,Alberto Bosi,Enrico Conca,Andrea Giudice,Alessandro Ruggeri,Simone Tisa,Alexander Flocke,B. Rosinski,Jean-Marc Dinten,Mathieu Perriollat,Christophe Fraschini,Jonathan Lavaud,Simon R. Arridge,Giuseppe Di Sciacca,Andrea Farina,Pietro Panizza,Elena Venturini,P.M. Gordebeke,Paola Taroni +22 more
TL;DR: In this article , a machine learning classification algorithm is applied to the SOLUS database to discriminate benign and malignant breast lesions, based on absorption and composition properties retrieved through diffuse optical tomography.
Proceedings ArticleDOI
Unifying global and local statistical measures for anatomy-guided emission tomography reconstruction
Kathleen Vunckx,Simon R. Arridge,Alexandre Bousse,Daniil Kazantsev,Stefano Pedemonte,Sebastien Ourselin,Brian Hutton +6 more
TL;DR: A new anatomy-guided reconstruction algorithm that has the additional advantage of estimating the underlying tissue classes jointly from the functional and anatomical information, such that errors in the a priori segmentation are expected to cause less artifacts than methods relying on a fixed predefined segmentation.
Proceedings ArticleDOI
Time-resolved Diffuse Optical Tomography based on Single pixel camera
Andrea Farina,Marta M. Betcke,Nicolas Ducros,Laura Di Sieno,Andrea Bassi,Antonio Pifferi,Gianluca Valentini,Simon R. Arridge,Cosimo D'Andrea +8 more
TL;DR: In this paper, a time-resolved DOT system based on rotating view acquisition and data sampling in compressed illumination/detection space is proposed and implemented and reconstruction on tissue mimicking phantoms with absorbing inclusions is presented.