Andreas Hauptmann

2.2k total citations
48 papers, 1.3k citations indexed

About

Andreas Hauptmann is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering. According to data from OpenAlex, Andreas Hauptmann has authored 48 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Biomedical Engineering, 22 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Electrical and Electronic Engineering. Recurrent topics in Andreas Hauptmann's work include Photoacoustic and Ultrasonic Imaging (12 papers), Medical Imaging Techniques and Applications (11 papers) and Electrical and Bioimpedance Tomography (11 papers). Andreas Hauptmann is often cited by papers focused on Photoacoustic and Ultrasonic Imaging (12 papers), Medical Imaging Techniques and Applications (11 papers) and Electrical and Bioimpedance Tomography (11 papers). Andreas Hauptmann collaborates with scholars based in United Kingdom, Finland and United States. Andreas Hauptmann's co-authors include Sarah Jane Hamilton, Ben Cox, Simon Arridge, Felix Lucka, Jennifer A. Steeden, Vivek Muthurangu, Jonas Adler, Sébastien Ourselin, Marta M. Betcke and Nam Huynh and has published in prestigious journals such as Bioinformatics, Journal of Computational Physics and Magnetic Resonance in Medicine.

In The Last Decade

Andreas Hauptmann

47 papers receiving 1.3k citations

Peers

Andreas Hauptmann

RNMI

EEE

GEOPH

Oliver Dorn Spain

Tanja Tarvainen Finland

Steven A. Johnson United States

Prabhat Munshi India

A.E. Yagle United States

Jiří Jaroš Czechia

Stephen Pistorius Canada

Andreas Rieder Germany

H. Gemmeke Germany

Raffaele Solimene Italy

Oliver Dorn Spain

Andreas Hauptmann

867 ×1.4

396 ×0.8

RNMI

412 ×1.0

EEE

298 ×0.8

325 ×2.4

GEOPH

Citations per year, relative to Andreas Hauptmann Andreas Hauptmann (= 1×) peers Oliver Dorn

Countries citing papers authored by Andreas Hauptmann

Since Specialization

Citations

This map shows the geographic impact of Andreas Hauptmann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andreas Hauptmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Hauptmann more than expected).

Fields of papers citing papers by Andreas Hauptmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andreas Hauptmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andreas Hauptmann. The network helps show where Andreas Hauptmann may publish in the future.

Co-authorship network of co-authors of Andreas Hauptmann

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Hauptmann. A scholar is included among the top collaborators of Andreas Hauptmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andreas Hauptmann. Andreas Hauptmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Cox, Ben, et al.. (2024). Compensating unknown speed of sound in learned fast 3D limited-view photoacoustic tomography. Photoacoustics. 37. 100597–100597. 1 indexed citations

Nissilä, Ilkka, et al.. (2024). Diffuse optical tomography of the brain: effects of inaccurate baseline optical parameters and refinements using learned post-processing. Biomedical Optics Express. 15(8). 4470–4470. 3 indexed citations

Springer, Sebastian, Aldo Glielmo, Tomi Kauppi, et al.. (2023). Reconstruction and segmentation from sparse sequential X-ray measurements of wood logs. 1(1). 1–20. 1 indexed citations

Hauptmann, Andreas, et al.. (2023). Domain independent post-processing with graph U-nets: applications to electrical impedance tomographic imaging⋆. Physiological Measurement. 44(12). 125008–125008. 9 indexed citations

Alles, Erwin J., Efthymios Maneas, Simon Arridge, et al.. (2022). Neural network Kalman filtering for 3D object tracking from linear array ultrasound data. University of Oulu Repository (University of Oulu). 9 indexed citations

Arridge, Simon, et al.. (2022). Joint reconstruction and low-rank decomposition for dynamic inverse problems. University of Oulu Repository (University of Oulu). 10 indexed citations

Virtanen, Ilkka, et al.. (2022). Hierarchical deconvolution for incoherent scatter radar data. Atmospheric measurement techniques. 15(12). 3843–3857. 1 indexed citations

Maneas, Efthymios, Andreas Hauptmann, Erwin J. Alles, et al.. (2022). Enhancement of instrumented ultrasonic tracking images using deep learning. International Journal of Computer Assisted Radiology and Surgery. 18(2). 395–399. 2 indexed citations

Lunz, Sebastian, Andreas Hauptmann, Tanja Tarvainen, Carola‐Bibiane Schönlieb, & Simon Arridge. (2021). On learned operator correction in inverse problems. University of Oulu Repository (University of Oulu). 24 indexed citations

10.

Muthurangu, Vivek, et al.. (2021). Machine learning in Magnetic Resonance Imaging:image reconstruction. University of Oulu Repository (University of Oulu). 37 indexed citations

11.

Hauptmann, Andreas, et al.. (2021). A model-based iterative learning approach for diffuse optical tomography. University of Oulu Repository (University of Oulu). 22 indexed citations

12.

Abascal, Juan, Nicolas Ducros, Simon Rit, et al.. (2021). Material Decomposition in Spectral CT Using Deep Learning: A Sim2Real Transfer Approach. IEEE Access. 9. 25632–25647. 3 indexed citations

13.

Rowe, Daniel B., et al.. (2021). Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems. IEEE Transactions on Computational Imaging. 7. 1341–1353. 38 indexed citations

14.

Roininen, Lassi, et al.. (2020). Blind hierarchical deconvolution. University of Oulu Repository (University of Oulu). 3 indexed citations

15.

Steeden, Jennifer A., Michael A. Quail, Alexander Gotschy, et al.. (2020). Rapid whole-heart CMR with single volume super-resolution. University of Oulu Repository (University of Oulu). 51 indexed citations

16.

Arridge, Simon & Andreas Hauptmann. (2020). Networks for nonlinear diffusion problems in imaging. University of Oulu Repository (University of Oulu). 13 indexed citations

17.

Hauptmann, Andreas, Jonas Adler, Simon Arridge, & Ozan Öktem. (2020). Multi-scale learned iterative reconstruction. University of Oulu Repository (University of Oulu). 9 indexed citations

18.

Hauptmann, Andreas, Simon Arridge, Felix Lucka, Vivek Muthurangu, & Jennifer A. Steeden. (2018). Real-time Cardiovascular MR with Spatio-temporal De-aliasing using Deep Learning - Proof of Concept in Congenital Heart Disease. arXiv (Cornell University). 1 indexed citations

19.

Hämäläinen, K., et al.. (2014). Total variation regularization for large-scale X-ray tomography. 25(1). 1–25. 11 indexed citations

20.

Hauptmann, Andreas, et al.. (1999). The Beginnings of Metallurgy. UCL Discovery (University College London). 39 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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