Tobias Lasser

2.1k total citations
86 papers, 1.3k citations indexed

About

Tobias Lasser is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Radiation. According to data from OpenAlex, Tobias Lasser has authored 86 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Radiology, Nuclear Medicine and Imaging, 44 papers in Biomedical Engineering and 32 papers in Radiation. Recurrent topics in Tobias Lasser's work include Medical Imaging Techniques and Applications (37 papers), Advanced X-ray and CT Imaging (29 papers) and Advanced X-ray Imaging Techniques (19 papers). Tobias Lasser is often cited by papers focused on Medical Imaging Techniques and Applications (37 papers), Advanced X-ray and CT Imaging (29 papers) and Advanced X-ray Imaging Techniques (19 papers). Tobias Lasser collaborates with scholars based in Germany, United States and Switzerland. Tobias Lasser's co-authors include Vasilis Ntziachristos, Franz Pfeiffer, Nassir Navab, Kevin L. Nelson, Antoine Soubret, Jorge Ripoll, Nikolaos C. Deliolanis, Damon E. Hyde, Florian Schaff and Sibylle Ziegler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Applied Physics Letters.

In The Last Decade

Tobias Lasser

83 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
Tobias Lasser Germany 18 707 562 350 155 129 86 1.3k
David Fuentes United States 23 747 1.1× 589 1.0× 130 0.4× 89 0.6× 159 1.2× 113 1.9k
Guobao Wang United States 23 1.5k 2.1× 554 1.0× 273 0.8× 191 1.2× 78 0.6× 123 2.0k
Mario Ries Netherlands 25 1.5k 2.2× 925 1.6× 209 0.6× 74 0.5× 81 0.6× 68 2.5k
Hervé Saint‐Jalmes France 23 1.3k 1.8× 769 1.4× 127 0.4× 87 0.6× 35 0.3× 113 2.0k
Jingfei Ma United States 30 2.1k 3.0× 303 0.5× 176 0.5× 86 0.6× 179 1.4× 121 3.1k
Jovan G. Brankov United States 20 920 1.3× 745 1.3× 520 1.5× 265 1.7× 31 0.2× 131 1.6k
Justin Lee United States 17 168 0.2× 601 1.1× 251 0.7× 307 2.0× 177 1.4× 45 1.6k
Dong Liang China 24 1.2k 1.8× 317 0.6× 315 0.9× 179 1.2× 77 0.6× 145 1.9k
Baudouin Denis de Senneville France 33 2.3k 3.2× 1.7k 3.0× 677 1.9× 163 1.1× 79 0.6× 135 3.3k

Countries citing papers authored by Tobias Lasser

Since Specialization
Citations

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

Fields of papers citing papers by Tobias Lasser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tobias Lasser. 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 Tobias Lasser. The network helps show where Tobias Lasser may publish in the future.

Co-authorship network of co-authors of Tobias Lasser

This figure shows the co-authorship network connecting the top 25 collaborators of Tobias Lasser. A scholar is included among the top collaborators of Tobias Lasser 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 Tobias Lasser. Tobias Lasser 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.
Hofmann, Felix, Theresa Urban, Franz Pfeiffer, et al.. (2024). Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imaging. Computers in Biology and Medicine. 185. 109533–109533. 4 indexed citations
2.
Tang, Peng, Xintong Yan, Nan Yang, et al.. (2024). Joint-individual fusion structure with fusion attention module for multi-modal skin cancer classification. Pattern Recognition. 154. 110604–110604. 9 indexed citations
3.
Viermetz, Manuel, et al.. (2024). Robust Sample Information Retrieval in Dark-Field Computed Tomography With a Vibrating Talbot-Lau Interferometer. IEEE Transactions on Medical Imaging. 43(11). 3820–3829. 1 indexed citations
4.
Koehler, Thomas, et al.. (2024). Streak artefact removal in x‐ray dark‐field computed tomography using a convolutional neural network. Medical Physics. 51(10). 7404–7414.
5.
Lasser, Tobias, et al.. (2024). Improving Automated Hemorrhage Detection at Sparse-View CT via U-Net–based Artifact Reduction. Radiology Artificial Intelligence. 6(4). e230275–e230275. 4 indexed citations
6.
Pfeiffer, Franz, et al.. (2023). WNet: A Data-Driven Dual-Domain Denoising Model for Sparse-View Computed Tomography With a Trainable Reconstruction Layer. IEEE Transactions on Computational Imaging. 9. 120–132. 24 indexed citations
7.
Viermetz, Manuel, et al.. (2023). Advanced Phase-Retrieval for Stepping-Free X-Ray Dark-Field Computed Tomography. IEEE Transactions on Medical Imaging. 42(10). 2876–2885. 6 indexed citations
8.
Hofmann, Florian, Theresa Urban, Friedrich Pfeiffer, et al.. (2023). Optimizing Convolutional Neural Networks for Chronic Obstructive Pulmonary Disease Detection in Clinical Computed Tomography Imaging. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 195(S 01). S35–S35. 3 indexed citations
9.
Symvoulidis, Panagiotis, et al.. (2023). Fast light-field 3D microscopy with out-of-distribution detection and adaptation through conditional normalizing flows. Biomedical Optics Express. 15(2). 1219–1219. 2 indexed citations
10.
Schielein, Maximilian, et al.. (2023). Outlier detection in dermatology: Performance of different convolutional neural networks for binary classification of inflammatory skin diseases. Journal of the European Academy of Dermatology and Venereology. 37(5). 1071–1079. 14 indexed citations
11.
Viermetz, Manuel, Pascal Meyer, F. Bergner, et al.. (2022). Dark-field computed tomography reaches the human scale. Proceedings of the National Academy of Sciences. 119(8). 56 indexed citations
12.
Schaff, Florian, et al.. (2022). X-ray computed tomography with seven degree of freedom robotic sample holder. Engineering Research Express. 4(3). 35022–35022. 10 indexed citations
13.
Viermetz, Manuel, et al.. (2022). Modeling Vibrations of a Tiled Talbot-Lau Interferometer on a Clinical CT. IEEE Transactions on Medical Imaging. 42(3). 774–784. 7 indexed citations
14.
Lyck, Ruth, et al.. (2021). Learning to Reconstruct Confocal Microscopy Stacks From Single Light Field Images. IEEE Transactions on Computational Imaging. 7. 775–788. 24 indexed citations
15.
Gorpas, Dimitris, Maximilian Koch, Evangelos Liapis, et al.. (2019). Fluorescence imaging reversion using spatially variant deconvolution. Scientific Reports. 9(1). 18123–18123. 6 indexed citations
16.
Symvoulidis, Panagiotis, et al.. (2019). Artifact-free deconvolution in light field microscopy. Optics Express. 27(22). 31644–31644. 39 indexed citations
17.
Schaff, Florian, et al.. (2018). Brain Connectivity Exposed by Anisotropic X-ray Dark-field Tomography. Scientific Reports. 8(1). 14345–14345. 14 indexed citations
18.
Seyyedi, Saeed, et al.. (2018). Low-Dose CT Perfusion of the Liver Using Reconstruction of Difference. IEEE Transactions on Radiation and Plasma Medical Sciences. 2(3). 205–214. 6 indexed citations
19.
Symvoulidis, Panagiotis, Antonella Lauri, Steffen Schneider, et al.. (2017). NeuBtracker—imaging neurobehavioral dynamics in freely behaving fish. Nature Methods. 14(11). 1079–1082. 25 indexed citations
20.
Nelson, Kevin L., et al.. (1995). Clinical safety of gadopentetate dimeglumine.. Radiology. 196(2). 439–443. 170 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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