Kees Joost Batenburg

7.2k total citations · 2 hit papers
151 papers, 5.1k citations indexed

About

Kees Joost Batenburg is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kees Joost Batenburg has authored 151 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Radiology, Nuclear Medicine and Imaging, 70 papers in Biomedical Engineering and 48 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kees Joost Batenburg's work include Medical Imaging Techniques and Applications (88 papers), Advanced X-ray and CT Imaging (59 papers) and Advanced X-ray Imaging Techniques (31 papers). Kees Joost Batenburg is often cited by papers focused on Medical Imaging Techniques and Applications (88 papers), Advanced X-ray and CT Imaging (59 papers) and Advanced X-ray Imaging Techniques (31 papers). Kees Joost Batenburg collaborates with scholars based in Netherlands, Belgium and France. Kees Joost Batenburg's co-authors include Jan Sijbers, Willem Jan Palenstijn, Sara Bals, Wim van Aarle, Jan De Beenhouwer, Gustaaf Van Tendeloo, Daniël M. Pelt, Thomas Altantzis, Folkert Bleichrodt and Sandra Van Aert and has published in prestigious journals such as Nature, Advanced Materials and SHILAP Revista de lepidopterología.

In The Last Decade

Kees Joost Batenburg

144 papers receiving 5.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Fast and flexible X-ray tomography using the ASTRA toolbox

2016 712 citations Wim van Aarle, Willem Jan Palenstijn et al. profile →
The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography

2015 660 citations Wim van Aarle, Willem Jan Palenstijn et al. Ultramicroscopy profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kees Joost Batenburg Netherlands	33	1.8k	1.8k	1.1k	980	900	151	5.1k
D. Van Dyck Belgium	46	1.2k 0.7×	1.0k 0.6×	2.4k 2.3×	1.6k 1.7×	1.9k 2.2×	277	7.7k
Manuel Guizar‐Sicairos Switzerland	50	1.7k 0.9×	675 0.4×	2.0k 1.8×	4.4k 4.5×	482 0.5×	178	8.9k
Timm Weitkamp France	39	2.3k 1.2×	1.3k 0.7×	990 0.9×	5.1k 5.2×	169 0.2×	194	6.9k
Yoshio Suzuki Japan	36	1.1k 0.6×	617 0.3×	706 0.7×	2.9k 3.0×	230 0.3×	286	5.7k
Ana Díaz Switzerland	40	1.3k 0.7×	474 0.3×	1.4k 1.3×	3.8k 3.9×	320 0.4×	172	6.0k
J. Baruchel France	40	1.8k 1.0×	759 0.4×	712 0.7×	3.0k 3.1×	199 0.2×	249	7.5k
Timur E. Gureyev Australia	40	3.0k 1.6×	1.5k 0.9×	1.4k 1.3×	6.7k 6.8×	241 0.3×	151	8.5k
Christian G. Schroer Germany	40	1.1k 0.6×	398 0.2×	1.5k 1.4×	3.5k 3.6×	403 0.4×	215	5.6k
A. W. Stevenson Australia	32	1.7k 0.9×	1.2k 0.7×	637 0.6×	4.1k 4.2×	104 0.1×	140	5.3k
Willem Jan Palenstijn Netherlands	16	1.0k 0.5×	1.0k 0.6×	257 0.2×	653 0.7×	172 0.2×	38	2.3k

Countries citing papers authored by Kees Joost Batenburg

Since Specialization

Citations

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

Fields of papers citing papers by Kees Joost Batenburg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kees Joost Batenburg. 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 Kees Joost Batenburg. The network helps show where Kees Joost Batenburg may publish in the future.

Co-authorship network of co-authors of Kees Joost Batenburg

This figure shows the co-authorship network connecting the top 25 collaborators of Kees Joost Batenburg. A scholar is included among the top collaborators of Kees Joost Batenburg 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 Kees Joost Batenburg. Kees Joost Batenburg 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

Batenburg, Kees Joost, et al.. (2024). Orchid fruit and root movement analyzed using 2D photographs and a bioinformatics pipeline for processing sequential 3D scans. Applications in Plant Sciences. 12(1). e11567–e11567. 1 indexed citations

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

Liere, Robert van, et al.. (2023). CT-based data generation for foreign object detection on a single X-ray projection. Scientific Reports. 13(1). 1881–1881. 7 indexed citations

Werkhoven, Ben van, et al.. (2022). Benchmarking Optimization Algorithms for Auto-Tuning GPU Kernels. IEEE Transactions on Evolutionary Computation. 27(3). 550–564. 5 indexed citations

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

Hermens, Erma, et al.. (2021). The Study of Three-Dimensional Fingerprint Recognition in Cultural Heritage. Journal on Computing and Cultural Heritage. 14(4). 1–20. 11 indexed citations

Schmidt, Maximilian, Poulami Somanya Ganguly, Sophia Bethany Coban, et al.. (2021). Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications. Journal of Imaging. 7(3). 44–44. 31 indexed citations

Palenstijn, Willem Jan, et al.. (2019). Prototyping X-ray tomographic reconstruction pipelines with FleXbox. SoftwareX. 11. 100364–100364. 14 indexed citations

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

10.

Palenstijn, Willem Jan, et al.. (2018). EDS tomographic reconstruction regularized by total nuclear variation joined with HAADF-STEM tomography. Ultramicroscopy. 191. 34–43. 14 indexed citations

11.

Carlo, Francesco De, Doğa Gürsoy, Kees Joost Batenburg, et al.. (2017). TomoBank: a tomographic data repository for computational x-ray science. Measurement Science and Technology. 29(3). 34004–34004. 65 indexed citations

12.

Jinnai, Hiroshi, Rafal E. Dunin–Borkowski, Vadim Migunov, et al.. (2017). Automated discrete electron tomography – Towards routine high-fidelity reconstruction of nanomaterials. Ultramicroscopy. 175. 87–96. 23 indexed citations

13.

Bladt, Eva, Daniël M. Pelt, Sara Bals, & Kees Joost Batenburg. (2015). Electron tomography based on highly limited data using a neural network reconstruction technique. Ultramicroscopy. 158. 81–88. 26 indexed citations

14.

Gardner, Richard J., et al.. (2013). Geometric reconstruction methods for electron tomography. Ultramicroscopy. 128. 42–54. 18 indexed citations

15.

Aarle, Wim van, Kees Joost Batenburg, & Jan Sijbers. (2012). Automatic Parameter Estimation for the Discrete Algebraic Reconstruction Technique (DART). IEEE Transactions on Image Processing. 21(11). 4608–4621. 41 indexed citations

16.

Batenburg, Kees Joost, et al.. (2012). Accurate segmentation of dense nanoparticles by partially discrete electron tomography. Ultramicroscopy. 114. 96–105. 32 indexed citations

17.

Batenburg, Kees Joost, et al.. (2012). Bounds on the quality of reconstructed images in binary tomography. Discrete Applied Mathematics. 161(15). 2236–2251. 8 indexed citations

18.

Batenburg, Kees Joost & Jan Sijbers. (2008). Generic iterative subset algorithms for discrete tomography. Discrete Applied Mathematics. 157(3). 438–451. 17 indexed citations

19.

Batenburg, Kees Joost & Walter A. Kosters. (2005). Neural networks for discrete tomography. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 18–19. 1 indexed citations

20.

Batenburg, Kees Joost. (2005). An evolutionary algorithm for discrete tomography. Discrete Applied Mathematics. 151(1-3). 36–54. 40 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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