Matthias J. Ehrhardt

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Carola-Bibiane SchönliebDAMTP, University of Cambridge確認したメールアドレス: cam.ac.uk
Simon ARRIDGEUniversity College London確認したメールアドレス: cs.ucl.ac.uk
Kris ThielemansProfessor in Medical Imaging Physics, UCL確認したメールアドレス: ucl.ac.uk
David AtkinsonProfessor, University College London確認したメールアドレス: ucl.ac.uk
Pawel J MarkiewiczUniversity College London, London South Bank Univeristy確認したメールアドレス: ucl.ac.uk
Martin BenningProfessor of Inverse Problems, University College London確認したメールアドレス: ucl.ac.uk
Sebastien OurselinProfessor of Healthcare Engineering, King's College London確認したメールアドレス: kcl.ac.uk
Luis PizarroResearch Associate, University College London確認したメールアドレス: ucl.ac.uk
Elena CelledoniProfessor of mathematics at the Norwegian University of Science and Technology確認したメールアドレス: math.ntnu.no
Brynjulf OwrenProfessor of Mathematics, NTNU, Norway確認したメールアドレス: ntnu.no
Ferdia SherryMaths + ML Researcher確認したメールアドレス: ferdiasherry.com
Antonin ChambolleCEREMADE, CNRS & Université Paris-Dauphine, PSL Research University確認したメールアドレス: ceremade.dauphine.fr
Marta M. BetckeUniversity College London確認したメールアドレス: ucl.ac.uk
Peter RichtarikProfessor, KAUST確認したメールアドレス: kaust.edu.sa
Lindon RobertsSchool of Mathematics and Statistics, University of Sydney確認したメールアドレス: sydney.edu.au
Anna BarnesPrincipal Research Fellow - King's College London確認したメールアドレス: kcl.ac.uk
Leon BungertInstitute of Mathematics, University of Würzburg確認したメールアドレス: uni-wuerzburg.de
Evgueni OvtchinnikovSenior Computational Scientist, Rutherford-Appleton Lab, UKRI-STFC確認したメールアドレス: stfc.ac.uk
Edoardo PascaHead of Computed Tomography, Science Technology Facilities Council確認したメールアドレス: stfc.ac.uk
Neill D.F. CampbellRoyal Society Industry Fellow and Professor at the University of Bath確認したメールアドレス: bath.ac.uk

フォロー

Matthias J. Ehrhardt

Mathematical Sciences, University of Bath

確認したメールアドレス: bath.ac.uk - ホームページ

Mathematics Inverse Problems Medical Imaging Optimization Machine Learning


タイトル引用回数順公開年順タイトル順	引用先引用先	年
Stochastic primal-dual hybrid gradient algorithm with arbitrary sampling and imaging applications A Chambolle, MJ Ehrhardt, P Richtárik, CB Schönlieb SIAM Journal on Optimization 28 (4), 2783-2808, 2018	210	2018
Joint reconstruction of PET-MRI by exploiting structural similarity MJ Ehrhardt, K Thielemans, L Pizarro, D Atkinson, S Ourselin, BF Hutton, ... Inverse Problems 31 (1), 015001, 2015	176	2015
Multicontrast MRI Reconstruction with Structure-Guided Total Variation MJ Ehrhardt, MM Betcke SIAM Journal on Imaging Sciences 9 (3), 1084-1106, 2016	144	2016
PET Reconstruction with an Anatomical MRI Prior using Parallel Level Sets. MJ Ehrhardt, P Markiewicz, M Liljeroth, A Barnes, V Kolehmainen, ... IEEE Transactions on Medical Imaging, 2016	119	2016
Deep learning as optimal control problems: models and numerical methods M Benning, E Celledoni, MJ Ehrhardt, B Owren, CB Schönlieb Journal of Computational Dynamics 6 (2), 171-198, 2019	102	2019
Learning the sampling pattern for MRI F Sherry, M Benning, JC De los Reyes, MJ Graves, G Maierhofer, ... IEEE Transactions on Medical Imaging, 2020	85	2020
Vector-valued image processing by parallel level sets MJ Ehrhardt, SR Arridge IEEE Transactions on Image Processing 23 (1), 9-18, 2014	79	2014
Blind image fusion for hyperspectral imaging with the directional total variation L Bungert, DA Coomes, MJ Ehrhardt, J Rasch, R Reisenhofer, ... Inverse Problems 34 (4), 044003, 2018	65	2018
Sirf: Synergistic image reconstruction framework E Ovtchinnikov, R Brown, C Kolbitsch, E Pasca, C da Costa-Luis, ... Computer Physics Communications 249, 107087, 2020	64	2020
NiftyPET: a high-throughput software platform for high quantitative accuracy and precision PET imaging and analysis PJ Markiewicz, MJ Ehrhardt, K Erlandsson, PJ Noonan, A Barnes, ... Neuroinformatics 16, 95-115, 2018	58	2018
Structure-preserving deep learning E Celledoni, MJ Ehrhardt, C Etmann, RI McLachlan, B Owren, ... European Journal of Applied Mathematics 32 (5), 888-936, 2021	56	2021
Regularising inverse problems with generative machine learning models MAG Duff, NDF Campbell, MJ Ehrhardt Journal of Mathematical Imaging and Vision 66 (1), 37-56, 2024	43	2024
Faster PET reconstruction with non-smooth priors by randomization and preconditioning MJ Ehrhardt, PJ Markiewicz, CB Schönlieb Physics in Medicine & Biology, 2019	41	2019
Choose your path wisely: gradient descent in a Bregman distance framework M Benning, MM Betcke, MJ Ehrhardt, CB Schönlieb SIAM Journal on Imaging Sciences 14 (2), 814-843, 2021	35	2021
Equivariant neural networks for inverse problems E Celledoni, MJ Ehrhardt, C Etmann, B Owren, CB Schönlieb, F Sherry Inverse problems 37 (8), 085006, 2021	32	2021
Accelerating variance-reduced stochastic gradient methods D Driggs, MJ Ehrhardt, CB Schönlieb Mathematical Programming, 1-45, 2020	32	2020
Fast Quasi-Newton Algorithms for Penalized Reconstruction in Emission Tomography and Further Improvements via Preconditioning YJ Tsai, A Bousse, MJ Ehrhardt, CW Stearns, S Ahn, BF Hutton, S Arridge, ... IEEE transactions on medical imaging 37 (4), 1000-1010, 2018	31	2018
Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning D Chen, M Davies, MJ Ehrhardt, CB Schönlieb, F Sherry, J Tachella IEEE Signal Processing Magazine 40 (1), 134-147, 2023	30	2023
Inexact derivative-free optimization for bilevel learning MJ Ehrhardt, L Roberts Journal of Mathematical Imaging and Vision, 1-21, 2021	27	2021
A geometric integration approach to nonsmooth, nonconvex optimisation ES Riis, MJ Ehrhardt, GRW Quispel, CB Schönlieb Foundations of Computational Mathematics, 1-44, 2021	26	2021

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