Publications

You can also find my articles on my Google Scholar profile.

Submitted

Sequentially optimized projections in X-ray imaging
M. Burger, A. Hauptmann, T. Helin, N. Hyvönen, JP Puska
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Learning and correcting non-Gaussian model errors
D. Smyl, TN. Tallman, JA. Black, A. Hauptmann, D. Liu
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Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems
S. Arridge, P. Fernsel, A. Hauptmann
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On Learned Operator Correction
S. Lunz, A. Hauptmann, T. Tarvainen, CB. Schönlieb, S. Arridge
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Image reconstruction in dynamic inverse problems with temporal models
A. Hauptmann, O. Öktem, CB. Schönlieb
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Accepted

Deep Learning in Photoacoustic Tomography: Current approaches and future directions
A. Hauptmann, B. Cox
Accepted for Journal of Biomedical Optics, 2020. (Link)
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Blind hierarchical deconvolution
A. Arjas, L. Roininen, M. Sillanpää, A. Hauptmann
Accepted for IEEE Machine Learning and Signal Processing (MLSP), 2020.
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Convolutional Neural Network for Material Decomposition in Spectral CT scans
S. Bussod, JFP. Abascal, S. Arridge, A. Hauptmann, C. Chappard, N. Ducros, F. Peyrin
Accepted for 28th European Signal Processing Conference (EUSIPCO 2020), 2020.

Multi-Scale Learned Iterative Reconstruction
A. Hauptmann, J. Adler, S. Arridge, and O. Öktem
Accepted for IEEE Transactions on Computational Imaging, 2020. (Link)
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Published

2020

Towards accurate quantitative photoacoustic imaging: learning vascular blood oxygen saturation in 3D
C. Bench, A. Hauptmann, B. Cox
Published in Journal of Biomedical Optics, 2020. (Link)
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Rapid Whole-Heart CMR with Single Volume Super-resolution
JA. Steeden, M. Quail, A. Gotschy, K. Mortensen, A. Hauptmann, S. Arridge, R. Jones, and V. Muthurangu
Published in Journal of Cardiovascular Magnetic Resonance, 2020. (Link)
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On the unreasonable effectiveness of CNNs
A. Hauptmann and J. Adler
Published in (non peer-reviewed) technical report on TechRxiv, 2020. (Link)
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Material Decomposition problem in spectral CT: A transfer deep learning approach
J. Abascal, N. Ducros, V. Pronina, S. Bussod, A. Hauptmann, S. Arridge, P. Douek, F. Peyrin
Published in 2020 IEEE ISBI Workshops: Deep Learning for Biomedical Image Reconstruction, 2020. (Link)
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Estimation of dynamic SNP-heritability with Bayesian Gaussian process models
A. Arjas, A. Hauptmann, MJ. Sillanpää
Published in Bioinformatics, 2020. (Link)
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Networks for Nonlinear Diffusion Problems in Imaging
S. Arridge and A. Hauptmann
Published in Journal of Mathematical Imaging and Vision, 2020. (Link)
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2019

Beltrami-Net: Domain Independent Deep D-bar Learning for Absolute Imaging with Electrical Impedance Tomography (a-EIT)
S. Hamilton, A. Hänninen, A. Hauptmann, and V. Kolehmainen
Published in Physiological Measurement, 2019. (Link)
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Application of Proximal Alternating Linearized Minimization (PALM) and inertial PALM to dynamic 3D CT
N. Djurabekova, A. Goldberg, A. Hauptmann, D. Hawkes, G. Long, F. Lucka, and M. Betcke
Published in Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019. (Link)

Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning - proof of concept in congenital heart disease (Editor's pick)
A. Hauptmann, S. Arridge, F. Lucka, V. Muthurangu, and J. Steeden
Published in Magnetic Resonance in Medicine, 2019. (Link)
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Revealing cracks inside conductive bodies by electric surface measurements
A. Hauptmann, M. Ikehata, H. Itou, and S. Siltanen
Published in Inverse Problems, 2019. (Link)
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2018

Approximate k-space models and Deep Learning for fast photoacoustic reconstruction
A. Hauptmann, B. Cox, F. Lucka, N. Huynh, M. Betcke, P. Beard, and S. Arridge
Published in Machine Learning for Medical Image Reconstruction, 2018. (Link)
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Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With Deep Neural Networks
SJ. Hamilton and A. Hauptmann
Published in IEEE Transactions on Medical Imaging, 2018. (Link)
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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, S. Ourselin, S. Arridge
Published in IEEE Transactions on Medical Imaging, 2018. (Link)
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2017

A variational reconstruction method for undersampled dynamic X-ray tomography based on physical motion models
M. Burger, H. Dirks, L. Frerking, A. Hauptmann, T. Helin, and S. Siltanen
Published in Inverse Problems, 2017. (Link)
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Approximation of full-boundary data from partial-boundary electrode measurements
A. Hauptmann
Published in Inverse Problems, 2017. (Link)
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A Direct D-bar Method for Partial Boundary Data Electrical Impedance Tomography with A Priori Information
M. Alsaker, S. Hamilton, and A. Hauptmann
Published in Inverse Problems and Imaging, 2017. (Link)
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Direct inversion from partial-boundary data in electrical impedance tomography
A. Hauptmann, S. Santacesaria, S. Siltanen
Published in Inverse Problems, 2017. (Link)
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2014

A Data-Driven Edge-Preserving D-bar Method for Electrical Impedance Tomography
S. Hamilton, A. Hauptmann, and S. Siltanen
Published in Inverse Problems and Imaging, 2014. (Link)
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Total variation regularization for large-scale X-ray tomography
K. Hämäläinen, L. Harhanen, A. Hauptmann, A. Kallonen, E. Niemi, and S. Siltanen
Published in International Journal of Tomography and Simulation, 2014.
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