Felix Lucka

1.9k total citations
55 papers, 1.1k citations indexed

About

Felix Lucka is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Mechanics of Materials. According to data from OpenAlex, Felix Lucka has authored 55 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Radiology, Nuclear Medicine and Imaging, 34 papers in Biomedical Engineering and 14 papers in Mechanics of Materials. Recurrent topics in Felix Lucka's work include Photoacoustic and Ultrasonic Imaging (18 papers), Medical Imaging Techniques and Applications (17 papers) and Advanced X-ray and CT Imaging (14 papers). Felix Lucka is often cited by papers focused on Photoacoustic and Ultrasonic Imaging (18 papers), Medical Imaging Techniques and Applications (17 papers) and Advanced X-ray and CT Imaging (14 papers). Felix Lucka collaborates with scholars based in Netherlands, United Kingdom and Germany. Felix Lucka's co-authors include Simon Arridge, Ben Cox, Carsten H. Wolters, Andreas Hauptmann, Marta M. Betcke, Paul C. Beard, Nam Huynh, Martin Burger, Jennifer A. Steeden and Vivek Muthurangu and has published in prestigious journals such as NeuroImage, Scientific Reports and The Journal of the Acoustical Society of America.

In The Last Decade

Felix Lucka

50 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Felix Lucka Netherlands 17 550 543 242 238 192 55 1.1k
Hamid Behnam Iran 22 408 0.7× 603 1.1× 116 0.5× 426 1.8× 52 0.3× 116 1.4k
Soo Yeol Lee South Korea 26 978 1.8× 869 1.6× 189 0.8× 196 0.8× 93 0.5× 102 2.0k
Hartmut Brauer Germany 18 130 0.2× 220 0.4× 174 0.7× 231 1.0× 69 0.4× 87 961
Sergey N. Makarov United States 22 552 1.0× 211 0.4× 154 0.6× 172 0.7× 246 1.3× 132 1.7k
R. Martin Arthur United States 17 657 1.2× 540 1.0× 126 0.5× 227 1.0× 15 0.1× 55 1.4k
Rafeef Abugharbieh Canada 24 350 0.6× 490 0.9× 40 0.2× 210 0.9× 105 0.5× 110 1.7k
Leonardo M. Angelone United States 23 504 0.9× 914 1.7× 50 0.2× 359 1.5× 120 0.6× 56 1.5k
Jan Kybic Czechia 21 490 0.9× 950 1.7× 81 0.3× 320 1.3× 44 0.2× 107 2.3k
Oleg Michailovich Canada 22 317 0.6× 911 1.7× 156 0.6× 132 0.6× 28 0.1× 65 1.7k
Hiroki Tamura Japan 17 191 0.3× 200 0.4× 24 0.1× 189 0.8× 159 0.8× 155 1.6k

Countries citing papers authored by Felix Lucka

Since Specialization
Citations

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

Fields of papers citing papers by Felix Lucka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Felix Lucka

This figure shows the co-authorship network connecting the top 25 collaborators of Felix Lucka. A scholar is included among the top collaborators of Felix Lucka 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 Felix Lucka. Felix Lucka 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.
Biguri, Ander, et al.. (2025). Benchmarking learned algorithms for computed tomography image reconstruction tasks. Leiden Repository (Leiden University). 3(0). 1–43. 1 indexed citations
2.
Lucka, Felix, Jeroen Veltman, Hendrik A. Messal, et al.. (2025). Image analysis of patient data from the hybrid photoacoustic-ultrasound tomography system PAM3. University of Twente Research Information. 60–60. 1 indexed citations
3.
Kretzer, Christian, et al.. (2024). Task-Adaptive Angle Selection for Computed Tomography-Based Defect Detection. Journal of Imaging. 10(9). 208–208.
4.
Palenstijn, Willem Jan, et al.. (2024). ASTRA kernelkit: GPU-accelerated projectors for computed tomography using cupy. Leiden Repository (Leiden University). 2(1). 70–92.
5.
Huynh, Nam, Thomas J. Allen, Jiaqi Zhu, et al.. (2024). A fast all-optical 3D photoacoustic scanner for clinical vascular imaging. Nature Biomedical Engineering. 9(5). 638–655. 24 indexed citations
6.
Kim, Lucia, et al.. (2024). Automated three-dimensional image registration for longitudinal photoacoustic imaging. Journal of Biomedical Optics. 29(S1). S11515–S11515. 1 indexed citations
7.
Coban, Sophia Bethany, et al.. (2023). Just-in-time deep learning for real-time X-ray computed tomography. Scientific Reports. 13(1). 20070–20070. 5 indexed citations
8.
Coban, Sophia Bethany, et al.. (2023). 2DeteCT - A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning. Scientific Data. 10(1). 576–576. 10 indexed citations
9.
Lucka, Felix, et al.. (2023). Beam filtration for object-tailored X-ray CT of multi-material cultural heritage objects. Heritage Science. 11(1). 9 indexed citations
10.
Lucka, Felix, et al.. (2022). Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation. NeuroImage. 262. 119530–119530. 4 indexed citations
11.
Eijnatten, Maureen van, Leonardo Rundo, Kees Joost Batenburg, et al.. (2021). 3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning. Data Archiving and Networked Services (DANS). 10 indexed citations
12.
Arridge, Simon, Felix Lucka, Ben Cox, et al.. (2021). Photoacoustic Reconstruction Using Sparsity in Curvelet Frame: Image Versus Data Domain. IEEE Transactions on Computational Imaging. 7. 879–893. 7 indexed citations
13.
Lucka, Felix, et al.. (2019). A cone-beam X-ray computed tomography data collection designed for machine learning. UCL Discovery (University College London). 11 indexed citations
14.
Treeby, Bradley E., Felix Lucka, Eleanor Martin, & Ben Cox. (2018). Equivalent-Source Acoustic Holography for Projecting Measured Ultrasound Fields Through Complex Media. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 65(10). 1857–1864. 13 indexed citations
15.
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
16.
Lucka, Felix, et al.. (2018). Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity. NeuroImage. 188. 252–260. 10 indexed citations
17.
Arridge, Simon, Marta M. Betcke, Ben Cox, Felix Lucka, & Bradley E. Treeby. (2016). On the Adjoint Operator in Photoacoustic Tomography. UCL Discovery (University College London). 62 indexed citations
18.
Vorwerk, Johannes, Felix Lucka, Moritz Dannhauer, et al.. (2015). The role of blood vessels in high-resolution volume conductor head modeling of EEG. NeuroImage. 128. 193–208. 43 indexed citations
19.
Pursiainen, Sampsa, Felix Lucka, & Carsten H. Wolters. (2012). Complete electrode model in EEG: relationship and differences to the point electrode model. Physics in Medicine and Biology. 57(4). 999–1017. 30 indexed citations
20.
Lucka, Felix, Sampsa Pursiainen, Martin Burger, & Carsten H. Wolters. (2012). Hierarchical Bayesian inference for the EEG inverse problem using realistic FE head models: Depth localization and source separation for focal primary currents. NeuroImage. 61(4). 1364–1382. 66 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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