Felix Lucka

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Ben CoxUniversity College LondonEmail confirmado em ucl.ac.uk
Simon ARRIDGEUniversity College LondonEmail confirmado em cs.ucl.ac.uk
Marta M. BetckeUniversity College LondonEmail confirmado em ucl.ac.uk
Carsten H. WoltersProfessor of Neurosciences and Biomedical Engineering; University of Münster, GermanyEmail confirmado em uni-muenster.de
Kees Joost BatenburgProfessor of Imaging and VisualizationEmail confirmado em liacs.leidenuniv.nl
Andreas HauptmannAcademy Research Fellow & Associate Professor, University of OuluEmail confirmado em oulu.fi
Martin BurgerDeutsches Elektronen-Synchrotron DESY und Universität HamburgEmail confirmado em uni-hamburg.de
Sophia Bethany CobanPost-doctoral Researcher at the University of ManchesterEmail confirmado em manchester.ac.uk
Tristan van LeeuwenCentrum Wiskunde & InformaticaEmail confirmado em cwi.nl
Ümit AydinUniversity of ReadingEmail confirmado em reading.ac.uk
Maureen van EijnattenTeam Lead / Program Scientist, Dept. of Crop Data Science, KeyGene N.V.Email confirmado em keygene.com
Johannes VorwerkSenior Scientist, Biomedical Engineering @ University of InnsbruckEmail confirmado em uibk.ac.at
Jonas AdlerStaff Research Scientist, Google DeepMindEmail confirmado em google.com
Bradley TreebyUniversity College LondonEmail confirmado em ucl.ac.uk
Olumide OgunladeUniversity of BirminghamEmail confirmado em bham.ac.uk
Sampsa PursiainenTampere UniversityEmail confirmado em tuni.fi
Sumientra RampersadAssistant Professor of Physics, UMass BostonEmail confirmado em northeastern.edu
Seok LewOlivet Nazarene UniversityEmail confirmado em olivet.edu
Thom OostendorpAssociate Professor of Medical Physics, Radboud University Medical CenterEmail confirmado em radboudumc.nl
Jennifer SteedenUCLEmail confirmado em ucl.ac.uk

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Felix Lucka

Centrum Wiskunde & Informatica

Email confirmado em cwi.nl - Página inicial

inverse problems computational imaging tomography deep learning compressed sensing


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography A Hauptmann, F Lucka, M Betcke, N Huynh, J Adler, B Cox, P Beard, ... IEEE transactions on medical imaging 37 (6), 1382-1393, 2018	363	2018
Real‐time cardiovascular MR with spatio‐temporal artifact suppression using deep learning–proof of concept in congenital heart disease A Hauptmann, S Arridge, F Lucka, V Muthurangu, JA Steeden Magnetic resonance in medicine 81 (2), 1143-1156, 2019	246	2019
Simulating transcranial direct current stimulation with a detailed anisotropic human head model SM Rampersad, AM Janssen, F Lucka, Ü Aydin, B Lanfer, S Lew, ... IEEE Transactions on Neural Systems and Rehabilitation Engineering 22 (3 …, 2014	213	2014
Accelerated high-resolution photoacoustic tomography via compressed sensing S Arridge, P Beard, M Betcke, B Cox, N Huynh, F Lucka, O Ogunlade, ... Physics in Medicine & Biology 61 (24), 8908, 2016	156	2016
On the adjoint operator in photoacoustic tomography SR Arridge, MM Betcke, BT Cox, F Lucka, BE Treeby Inverse Problems 32 (11), 115012, 2016	120	2016
Hierarchical Bayesian inference for the EEG inverse problem using realistic FE head models: depth localization and source separation for focal primary currents F Lucka, S Pursiainen, M Burger, CH Wolters Neuroimage 61 (4), 1364-1382, 2012	100	2012
The role of blood vessels in high-resolution volume conductor head modeling of EEG LDJ Fiederer, J Vorwerk, F Lucka, M Dannhauer, S Yang, M Dümpelmann, ... NeuroImage 128, 193-208, 2016	66	2016
High resolution 3D ultrasonic breast imaging by time-domain full waveform inversion F Lucka, M Pérez-Liva, BE Treeby, BT Cox Inverse Problems 38 (2), 025008, 2021	55	2021
A cone-beam X-ray computed tomography data collection designed for machine learning H Der Sarkissian, F Lucka, M van Eijnatten, G Colacicco, SB Coban, ... Scientific Data 6 (1), 1-8, 2019	55	2019
Maximum a posteriori estimates in linear inverse problems with log-concave priors are proper Bayes estimators M Burger, F Lucka Inverse Problems 30 (11), 114004, 2014	54	2014
Approximate k-space models and Deep Learning for fast photoacoustic reconstruction A Hauptmann, B Cox, F Lucka, N Huynh, M Betcke, P Beard, S Arridge International Workshop on Machine Learning for Medical Image Reconstruction …, 2018	47	2018
Using reciprocity for relating the simulation of transcranial current stimulation to the EEG forward problem S Wagner, F Lucka, J Vorwerk, CS Herrmann, G Nolte, M Burger, ... NeuroImage 140, 163-173, 2016	47	2016
Enhancing compressed sensing 4D photoacoustic tomography by simultaneous motion estimation F Lucka, N Huynh, M Betcke, E Zhang, P Beard, B Cox, S Arridge SIAM Journal on Imaging Sciences 11 (4), 2224-2253, 2018	45	2018
Explorative Imaging and Its Implementation at the FleX-ray Laboratory SB Coban, F Lucka, WJ Palenstijn, D Van Loo, KJ Batenburg Journal of Imaging 6 (4), 18, 2020	44	2020
Complete electrode model in EEG: relationship and differences to the point electrode model S Pursiainen, F Lucka, CH Wolters Physics in Medicine & Biology 57 (4), 999, 2012	44	2012
The influence of sulcus width on simulated electric fields induced by transcranial magnetic stimulation AM Janssen, SM Rampersad, F Lucka, B Lanfer, S Lew, Ü Aydin, ... Physics in Medicine & Biology 58 (14), 4881, 2013	43	2013
Refraction-corrected ray-based inversion for three-dimensional ultrasound tomography of the breast A Javaherian, F Lucka, BT Cox Inverse Problems 36 (12), 125010, 2020	42	2020
Never look back-A modified EnKF method and its application to the training of neural networks without back propagation E Haber, F Lucka, L Ruthotto arXiv preprint arXiv:1805.08034, 2018	35	2018
Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors F Lucka Inverse Problems 28 (12), 125012, 2012	32	2012
Single-pixel camera photoacoustic tomography N Huynh, F Lucka, EZ Zhang, MM Betcke, SR Arridge, PC Beard, BT Cox Journal of Biomedical Optics 24 (12), 121907, 2019	26	2019

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