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


Sequentially optimized projections in X-ray imaging
M. Burger, A. Hauptmann, T. Helin, N. Hyvönen, JP Puska
Download here

Learning and correcting non-Gaussian model errors
D. Smyl, TN. Tallman, JA. Black, A. Hauptmann, D. Liu
Download here

Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems
S. Arridge, P. Fernsel, A. Hauptmann
Download here

On Learned Operator Correction
S. Lunz, A. Hauptmann, T. Tarvainen, CB. Schönlieb, S. Arridge
Download here

Image reconstruction in dynamic inverse problems with temporal models
A. Hauptmann, O. Öktem, CB. Schönlieb
Download here


Deep Learning in Photoacoustic Tomography: Current approaches and future directions
A. Hauptmann, B. Cox
Accepted for Journal of Biomedical Optics, 2020. (Link)
Download here

Blind hierarchical deconvolution
A. Arjas, L. Roininen, M. Sillanpää, A. Hauptmann
Accepted for IEEE Machine Learning and Signal Processing (MLSP), 2020.
Download here

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)
Download here



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)
Download here

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)
Download here

On the unreasonable effectiveness of CNNs
A. Hauptmann and J. Adler
Published in (non peer-reviewed) technical report on TechRxiv, 2020. (Link)
Download here

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)
Download here

Estimation of dynamic SNP-heritability with Bayesian Gaussian process models
A. Arjas, A. Hauptmann, MJ. Sillanpää
Published in Bioinformatics, 2020. (Link)
Download here

Networks for Nonlinear Diffusion Problems in Imaging
S. Arridge and A. Hauptmann
Published in Journal of Mathematical Imaging and Vision, 2020. (Link)
Download here


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)
Download here

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)
Download here

Revealing cracks inside conductive bodies by electric surface measurements
A. Hauptmann, M. Ikehata, H. Itou, and S. Siltanen
Published in Inverse Problems, 2019. (Link)
Download here


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)
Download here

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)
Download here

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)
Download here


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)
Download here

Approximation of full-boundary data from partial-boundary electrode measurements
A. Hauptmann
Published in Inverse Problems, 2017. (Link)
Download here

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)
Download here

Direct inversion from partial-boundary data in electrical impedance tomography
A. Hauptmann, S. Santacesaria, S. Siltanen
Published in Inverse Problems, 2017. (Link)
Download here


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)
Download here

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.
Download here