Andreas Hauptmann

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 58

Top Topics

Image Reconstruction

Inverse Problems

Top Venues

IEEE Trans. Medical Imaging

IEEE Trans. Computational Imaging

SIAM J. Imaging Sci.

Publications

Leatile Marata, Onel Luis Alcaraz López, Andreas Hauptmann, Hamza Djelouat, Hirley Alves
Joint Activity Detection and Channel Estimation for Clustered Massive Machine Type Communications. IEEE Trans. Wirel. Commun. 23 (6) (2024)
Andreas Hauptmann, Tanja Tarvainen
Model-based reconstructions for quantitative imaging in photoacoustic tomography. CoRR (2023)
Andreas Hauptmann, Jenni Poimala
Model-corrected learned primal-dual models for fast limited-view photoacoustic tomography. CoRR (2023)
Andreas Hauptmann, Subhadip Mukherjee, Carola-Bibiane Schönlieb, Ferdia Sherry
Convergent regularization in inverse problems and linear plug-and-play denoisers. CoRR (2023)
Arttu Arjas, Mikko J. Sillanpää, Andreas Hauptmann
Sequential model correction for nonlinear inverse problems. CoRR (2023)
William Herzberg, Andreas Hauptmann, Sarah Jane Hamilton
Domain independent post-processing with graph U-nets: Applications to Electrical Impedance Tomographic Imaging. CoRR (2023)
Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications. IEEE Signal Process. Mag. 40 (1) (2023)
Derick Nganyu Tanyu, Jianfeng Ning, Andreas Hauptmann, Bangti Jin, Peter Maass
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches. CoRR (2023)
Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Andreas Hauptmann, Carola-Bibiane Schönlieb
Robust Data-Driven Accelerated Mirror Descent. ICASSP (2023)
Efthymios Maneas, Andreas Hauptmann, Erwin J. Alles, Wenfeng Xia, Sacha Noimark, Anna L. David, Simon R. Arridge, Adrien E. Desjardins
Enhancement of instrumented ultrasonic tracking images using deep learning. Int. J. Comput. Assist. Radiol. Surg. 18 (2) (2023)
Simon R. Arridge, Andreas Hauptmann, Yury Korolev
Inverse Problems with Learned Forward Operators. CoRR (2023)
Arttu Arjas, Mikko J. Sillanpää, Andreas Hauptmann
Sequential Model Correction for Nonlinear Inverse Problems. SIAM J. Imaging Sci. 16 (4) (2023)
Satu I. Inkinen, Mikael A. K. Brix, Miika T. Nieminen, Simon R. Arridge, Andreas Hauptmann
Unsupervised denoising for sparse multi-spectral computed tomography. CoRR (2022)
Simo Särkkä, Lassi Roininen, Manon Kok, Roland Hostettler, Andreas Hauptmann
Guest Editorial: MLSP 2020 Special Issue. J. Signal Process. Syst. 94 (2) (2022)
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maass, Bangti Jin
An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. IEEE Trans. Computational Imaging 8 (2022)
Meghdoot Mozumder, Andreas Hauptmann, Ilkka Nissilä, Simon R. Arridge, Tanja Tarvainen
A Model-Based Iterative Learning Approach for Diffuse Optical Tomography. IEEE Trans. Medical Imaging 41 (5) (2022)
Anssi Manninen, Meghdoot Mozumder, Tanja Tarvainen, Andreas Hauptmann
Sparsity promoting reconstructions via hierarchical prior models in diffuse optical tomography. CoRR (2022)
Sebastian Springer, Aldo Glielmo, Angelina Senchukova, Tomi Kauppi, Jarkko Suuronen, Lassi Roininen, Heikki Haario, Andreas Hauptmann
Reconstruction and segmentation from sparse sequential X-ray measurements of wood logs. CoRR (2022)
Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem, Marcelo Pereyra, Carola-Bibiane Schönlieb
Learned reconstruction with convergence guarantees. CoRR (2022)
Juan F. P. J. Abascal, Nicolas Ducros, Valeriya Pronina, Simon Rit, Pierre-Antoine Rodesch, Thomas Broussaud, Suzanne Bussod, Philippe C. Douek, Andreas Hauptmann, Simon R. Arridge, Françoise Peyrin
Material Decomposition in Spectral CT Using Deep Learning: A Sim2Real Transfer Approach. IEEE Access 9 (2021)
William Herzberg, Daniel B. Rowe, Andreas Hauptmann, Sarah Jane Hamilton
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems. IEEE Trans. Computational Imaging 7 (2021)
Danny Smyl, Tyler N. Tallman, Jonathan A. Black, Andreas Hauptmann, Dong Liu
Learning and correcting non-Gaussian model errors. J. Comput. Phys. 432 (2021)
Arttu Arjas, Erwin J. Alles, Efthymios Maneas, Simon R. Arridge, Adrien E. Desjardins, Mikko J. Sillanpää, Andreas Hauptmann
Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data. CoRR (2021)
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin
Is Deep Image Prior in Need of a Good Education? CoRR (2021)
William Herzberg, Daniel B. Rowe, Andreas Hauptmann, Sarah Jane Hamilton
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems. CoRR (2021)
Riccardo Barbano, Zeljko Kereta, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
Unsupervised Knowledge-Transfer for Learned Image Reconstruction. CoRR (2021)
Sebastian Lunz, Andreas Hauptmann, Tanja Tarvainen, Carola-Bibiane Schönlieb, Simon R. Arridge
On Learned Operator Correction in Inverse Problems. SIAM J. Imaging Sci. 14 (1) (2021)
Danny Smyl, Tyler N. Tallman, Dong Liu, Andreas Hauptmann
An Efficient Quasi-Newton Method for Nonlinear Inverse Problems via Learned Singular Values. IEEE Signal Process. Lett. 28 (2021)
Arttu Arjas, Andreas Hauptmann, Mikko J. Sillanpää
Estimation of dynamic SNP-heritability with Bayesian Gaussian process models. Bioinform. 36 (12) (2020)
Andreas Hauptmann, Danny Smyl
Fusing electrical and elasticity imaging. CoRR (2020)
Arttu Arjas, Lassi Roininen, Mikko J. Sillanpää, Andreas Hauptmann
Blind Hierarchical Deconvolution. MLSP (2020)
Andreas Hauptmann, Jonas Adler, Simon R. Arridge, Ozan Öktem
Multi-Scale Learned Iterative Reconstruction. IEEE Trans. Computational Imaging 6 (2020)
Danny Smyl, Tyler N. Tallman, Dong Liu, Andreas Hauptmann
An efficient Quasi-Newton method for nonlinear inverse problems via learned singular values. CoRR (2020)
Suzanne Bussod, Juan F. P. J. Abascal, Simon R. Arridge, Andreas Hauptmann, Christine Chappard, Nicolas Ducros, Françoise Peyrin
Convolutional Neural Network for Material Decomposition in Spectral CT Scans. EUSIPCO (2020)
Danny Smyl, Tyler N. Tallman, Jonathan A. Black, Andreas Hauptmann, Dong Liu
Learning and correcting non-Gaussian model errors. CoRR (2020)
Arttu Arjas, Lassi Roininen, Mikko J. Sillanpää, Andreas Hauptmann
Blind hierarchical deconvolution. CoRR (2020)
Andreas Hauptmann, Ben T. Cox
Deep Learning in Photoacoustic Tomography: Current approaches and future directions. CoRR (2020)
Martin Burger, Andreas Hauptmann, Tapio Helin, Nuutti Hyvönen, Juha-Pekka Puska
Sequentially optimized projections in X-ray imaging. CoRR (2020)
Simon Robert Arridge, Pascal Fernsel, Andreas Hauptmann
Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems. CoRR (2020)
Andreas Hauptmann, Ozan Öktem, Carola Schönlieb
Image reconstruction in dynamic inverse problems with temporal models. CoRR (2020)
Javier Montalt-Tordera, Vivek Muthurangu, Andreas Hauptmann, Jennifer Anne Steeden
Machine Learning in Magnetic Resonance Imaging: Image Reconstruction. CoRR (2020)
Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon R. Arridge, Bangti Jin
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction. CoRR (2020)
Andreas Hauptmann, Jonas Adler
On the unreasonable effectiveness of CNNs. CoRR (2020)
Sebastian Lunz, Andreas Hauptmann, Tanja Tarvainen, Carola-Bibiane Schönlieb, Simon R. Arridge
On Learned Operator Correction. CoRR (2020)
Juan F. P. J. Abascal, Nicolas Ducros, Valeriya Pronina, Suzanne Bussod, Andreas Hauptmann, Simon R. Arridge, Philippe Douek, Françoise Peyrin
Material Decomposition Problem in Spectral CT: A Transfer Deep Learning Approach. ISBI Workshops (2020)
Simon R. Arridge, Andreas Hauptmann
Networks for Nonlinear Diffusion Problems in Imaging. J. Math. Imaging Vis. 62 (3) (2020)
Jennifer Anne Steeden, Michael Quail, Alexander Gotschy, Andreas Hauptmann, Simon R. Arridge, Rodney Jones, Vivek Muthurangu
Rapid Whole-Heart CMR with Single Volume Super-resolution. CoRR (2019)
Andreas Hauptmann, Jonas Adler, Simon R. Arridge, Ozan Öktem
Multi-Scale Learned Iterative Reconstruction. CoRR (2019)
Andreas Hauptmann, Ben T. Cox, Felix Lucka, Nam Huynh, Marta M. Betcke, Paul C. Beard, Simon R. Arridge
Approximate k-space models and Deep Learning for fast photoacoustic reconstruction. CoRR (2018)
Andreas Hauptmann, Ben T. Cox, Felix Lucka, Nam Huynh, Marta M. Betcke, Paul C. Beard, Simon R. Arridge
Approximate k-Space Models and Deep Learning for Fast Photoacoustic Reconstruction. MLMIR@MICCAI (2018)
Sarah Jane Hamilton, Asko Hänninen, Andreas Hauptmann, Ville Kolehmainen
Beltrami-Net: Domain Independent Deep D-bar Learning for Absolute Imaging with Electrical Impedance Tomography (a-EIT). CoRR (2018)
Andreas Hauptmann, Simon R. Arridge, Felix Lucka, Vivek Muthurangu, Jennifer Anne Steeden
Real-time Cardiovascular MR with Spatio-temporal De-aliasing using Deep Learning - Proof of Concept in Congenital Heart Disease. CoRR (2018)
Andreas Hauptmann, Felix Lucka, Marta M. Betcke, Nam Huynh, Jonas Adler, Ben T. Cox, Paul C. Beard, Sébastien Ourselin, Simon R. Arridge
Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography. IEEE Trans. Medical Imaging 37 (6) (2018)
Simon R. Arridge, Andreas Hauptmann
Networks for Nonlinear Diffusion Problems in Imaging. CoRR (2018)
Sarah Jane Hamilton, Andreas Hauptmann
Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With Deep Neural Networks. IEEE Trans. Medical Imaging 37 (10) (2018)
Andreas Hauptmann, Masaru Ikehata, Hiromichi Itou, Samuli Siltanen
Revealing cracks inside conductive bodies by electric surface measurements. CoRR (2018)
Sarah Jane Hamilton, Andreas Hauptmann
Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep Neural Networks. CoRR (2017)
Andreas Hauptmann, Felix Lucka, Marta M. Betcke, Nam Huynh, Ben T. Cox, Paul C. Beard, Sébastien Ourselin, Simon R. Arridge
Model based learning for accelerated, limited-view 3D photoacoustic tomography. CoRR (2017)