Lars G. Hanson

2.1k total citations
82 papers, 1.3k citations indexed

About

Lars G. Hanson is a scholar working on Radiology, Nuclear Medicine and Imaging, Atomic and Molecular Physics, and Optics and Biomedical Engineering. According to data from OpenAlex, Lars G. Hanson has authored 82 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Radiology, Nuclear Medicine and Imaging, 24 papers in Atomic and Molecular Physics, and Optics and 14 papers in Biomedical Engineering. Recurrent topics in Lars G. Hanson's work include Advanced MRI Techniques and Applications (44 papers), Atomic and Subatomic Physics Research (18 papers) and Functional Brain Connectivity Studies (13 papers). Lars G. Hanson is often cited by papers focused on Advanced MRI Techniques and Applications (44 papers), Atomic and Subatomic Physics Research (18 papers) and Functional Brain Connectivity Studies (13 papers). Lars G. Hanson collaborates with scholars based in Denmark, Germany and United States. Lars G. Hanson's co-authors include Axel Thielscher, Olaf B. Paulson, Hartwig R. Siebner, Hyunjoo J. Lee, Torben E. Lund, P. Lambropoulos, Egill Rostrup, Anina Ritterband‐Rosenbaum, Maria Willerslev‐Olsen and Glen A. Lichtwark and has published in prestigious journals such as Physical Review Letters, PLoS ONE and NeuroImage.

In The Last Decade

Lars G. Hanson

72 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lars G. Hanson Denmark 21 511 225 215 195 166 82 1.3k
Hermien E. Kan Netherlands 33 960 1.9× 366 1.6× 177 0.8× 117 0.6× 102 0.6× 114 3.1k
Paulo Loureiro de Sousa France 22 730 1.4× 205 0.9× 225 1.0× 208 1.1× 51 0.3× 68 1.8k
Johannes M. Hoogduin Netherlands 21 852 1.7× 149 0.7× 147 0.7× 739 3.8× 122 0.7× 41 1.9k
Michael Wyss Switzerland 20 625 1.2× 170 0.8× 125 0.6× 383 2.0× 73 0.4× 64 1.5k
Robert W. Prost United States 28 1.2k 2.4× 201 0.9× 92 0.4× 406 2.1× 118 0.7× 68 2.6k
Amy H. Herlihy United Kingdom 27 982 1.9× 111 0.5× 68 0.3× 224 1.1× 195 1.2× 48 2.7k
Ulrike Nöth Germany 24 878 1.7× 119 0.5× 114 0.5× 221 1.1× 113 0.7× 71 1.4k
Maarten J. Versluis Netherlands 28 1.2k 2.4× 193 0.9× 133 0.6× 412 2.1× 250 1.5× 64 2.2k
R. Marc Lebel Canada 27 1.0k 2.0× 166 0.7× 146 0.7× 384 2.0× 68 0.4× 46 1.9k
Guangyao Wu China 19 459 0.9× 109 0.5× 90 0.4× 298 1.5× 101 0.6× 96 1.2k

Countries citing papers authored by Lars G. Hanson

Since Specialization
Citations

This map shows the geographic impact of Lars G. Hanson'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 Lars G. Hanson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lars G. Hanson more than expected).

Fields of papers citing papers by Lars G. Hanson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lars G. Hanson. 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 Lars G. Hanson. The network helps show where Lars G. Hanson may publish in the future.

Co-authorship network of co-authors of Lars G. Hanson

This figure shows the co-authorship network connecting the top 25 collaborators of Lars G. Hanson. A scholar is included among the top collaborators of Lars G. Hanson 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 Lars G. Hanson. Lars G. Hanson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Arruda, Bailey, Tavis K. Anderson, Lars G. Hanson, et al.. (2025). Contemporary United States PRRSV 1-4-4 L1C.5 isolate causes severe disease comparable to historic highly pathogenic PRRSV. Virology. 615. 110748–110748.
2.
3.
Lerche, Mathilde H., Magnus Karlsson, Esben Søvsø Szocska Hansen, et al.. (2024). Hyperpolarized Water for Coronary Artery Angiography and Whole-Heart Myocardial Perfusion Quantification. Tomography. 10(7). 1113–1122. 1 indexed citations
4.
5.
Puonti, Oula, et al.. (2023). A head template for computational dose modelling for transcranial focused ultrasound stimulation. NeuroImage. 277. 120227–120227. 10 indexed citations
6.
Xue, Rong, et al.. (2022). Tracking of rigid head motion duringMRIusing an EEGsystem. Magnetic Resonance in Medicine. 88(2). 986–1001. 9 indexed citations
7.
Mahmood, Faisal, et al.. (2022). Decomposition-based framework for tumor classification and prediction of treatment response from longitudinal MRI. Physics in Medicine and Biology. 68(2). 25006–25006. 2 indexed citations
8.
Scheffler, Klaus, et al.. (2021). Sensitivity and resolution improvement for in vivo magnetic resonance current‐density imaging of the human brain. Magnetic Resonance in Medicine. 86(6). 3131–3146. 6 indexed citations
9.
Puonti, Oula, et al.. (2021). On the reconstruction of magnetic resonance current density images of the human brain: Pitfalls and perspectives. NeuroImage. 243. 118517–118517. 9 indexed citations
10.
Montanaro, Hazael, Hyunjoo J. Lee, Lars G. Hanson, et al.. (2020). Transducer modeling for accurate acoustic simulations of transcranial focused ultrasound stimulation. Journal of Neural Engineering. 17(4). 46010–46010. 24 indexed citations
11.
Pedersen, Jan, et al.. (2019). Inductive measurement and encoding of k-space trajectories in MR raw data. Magnetic Resonance Materials in Physics Biology and Medicine. 32(6). 655–667. 4 indexed citations
12.
Scheffler, Klaus, et al.. (2019). The stray magnetic fields in Magnetic Resonance Current Density Imaging (MRCDI). Physica Medica. 59. 142–150. 11 indexed citations
13.
Posse, Stefan, Lars G. Hanson, Annemarie T. Kristensen, et al.. (2018). Development of a Symmetric Echo-Planar Spectroscopy Imaging Framework for Hyperpolarized 13C Imaging in a Clinical PET/MR Scanner. Tomography. 4(3). 110–122. 7 indexed citations
14.
Hastrup, Nina, Sauzanne Khalilieh, David C. Dale, et al.. (2015). The effects of the CXCR2 antagonist, MK-7123, on bone marrow functions in healthy subjects. Cytokine. 72(2). 197–203. 12 indexed citations
15.
Stoltenberg, Michael, Olga Kubassova, Mikael Boesen, et al.. (2012). Dynamic gadolinium-enhanced magnetic resonance imaging allows accurate assessment of the synovial inflammatory activity in rheumatoid arthritis knee joints: a comparison with synovial histology. Scandinavian Journal of Rheumatology. 41(2). 89–94. 55 indexed citations
16.
Hanson, Lars G. & Anne‐Marie Russell. (2009). The Challenge of the Black Box: Technosocial Predictive Analytics (TPA) and the Real World.. National Conference on Artificial Intelligence. 55–58. 1 indexed citations
17.
Hanson, Lars G., et al.. (2007). Encoding of electrophysiology and other signals in MR images. Journal of Magnetic Resonance Imaging. 25(5). 1059–1066. 6 indexed citations
18.
Sørensen, Per Soelberg, A. Jønsson, Morten Blinkenberg, et al.. (2006). The relationship between MRI and PET changes and cognitive disturbances in MS. Journal of the Neurological Sciences. 245(1-2). 99–102. 12 indexed citations
19.
Jønsson, A., T Tscherning, Lars G. Hanson, et al.. (2006). Correlation of Global N-Acetyl Aspartate With Cognitive Impairment in Multiple Sclerosis. Archives of Neurology. 63(4). 533–533. 50 indexed citations
20.

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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