Cornelis H. Slump

5.5k total citations
264 papers, 3.6k citations indexed

About

Cornelis H. Slump is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Cornelis H. Slump has authored 264 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 108 papers in Radiology, Nuclear Medicine and Imaging, 60 papers in Biomedical Engineering and 51 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Cornelis H. Slump's work include Medical Imaging Techniques and Applications (59 papers), Advanced X-ray and CT Imaging (34 papers) and Cardiac Imaging and Diagnostics (30 papers). Cornelis H. Slump is often cited by papers focused on Medical Imaging Techniques and Applications (59 papers), Advanced X-ray and CT Imaging (34 papers) and Cardiac Imaging and Diagnostics (30 papers). Cornelis H. Slump collaborates with scholars based in Netherlands, United States and Germany. Cornelis H. Slump's co-authors include Willem Jan van Rooij, Javier Oliván Bescós, M. Sluzewski, D. Wijnalda, Henk A. Marquering, Charles B.L.M. Majoie, Roel Schiphorst, Geert J. Streekstra, Martijn F. Boomsma and R.H.H. Wellenberg and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Stroke.

In The Last Decade

Cornelis H. Slump

240 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cornelis H. Slump Netherlands 31 1.4k 879 876 692 555 264 3.6k
Xu Li China 34 1.1k 0.8× 416 0.5× 473 0.5× 428 0.6× 288 0.5× 204 4.0k
D. Rodney Hose United Kingdom 30 853 0.6× 535 0.6× 763 0.9× 187 0.3× 1.2k 2.1× 116 3.0k
Heinz Handels Germany 29 1.3k 0.9× 549 0.6× 786 0.9× 157 0.2× 329 0.6× 213 3.6k
George C. Kagadis Greece 34 1.0k 0.7× 1.3k 1.5× 527 0.6× 236 0.3× 959 1.7× 132 3.2k
Rebecca Fahrig United States 33 2.8k 2.0× 1.1k 1.3× 2.2k 2.5× 266 0.4× 290 0.5× 233 4.1k
Andrew P. King United Kingdom 31 1.5k 1.1× 327 0.4× 762 0.9× 121 0.2× 522 0.9× 190 3.7k
Nobuhiko Hata United States 39 1.4k 1.0× 872 1.0× 2.8k 3.2× 192 0.3× 1.4k 2.6× 169 5.1k
Frans N. van de Vosse Netherlands 46 1.5k 1.1× 2.2k 2.5× 2.5k 2.9× 290 0.4× 3.0k 5.4× 310 8.7k
Ke Sheng United States 40 2.7k 1.9× 2.6k 3.0× 719 0.8× 385 0.6× 665 1.2× 276 5.5k
Andrzej Materka Poland 22 2.0k 1.4× 570 0.6× 650 0.7× 73 0.1× 309 0.6× 85 3.7k

Countries citing papers authored by Cornelis H. Slump

Since Specialization
Citations

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

Fields of papers citing papers by Cornelis H. Slump

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cornelis H. Slump. 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 Cornelis H. Slump. The network helps show where Cornelis H. Slump may publish in the future.

Co-authorship network of co-authors of Cornelis H. Slump

This figure shows the co-authorship network connecting the top 25 collaborators of Cornelis H. Slump. A scholar is included among the top collaborators of Cornelis H. Slump 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 Cornelis H. Slump. Cornelis H. Slump 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
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Sırmaçek, Beril, et al.. (2023). Unsupervised convolutional autoencoders for 4D transperineal ultrasound classification. Journal of Medical Imaging. 10(1). 14004–14004. 5 indexed citations
3.
4.
Vriens, Dennis, Lioe‐Fee de Geus‐Oei, Cornelis H. Slump, et al.. (2022). [18F]FDG-PET/CT radiomics for the identification of genetic clusters in pheochromocytomas and paragangliomas. European Radiology. 32(10). 7227–7236. 13 indexed citations
5.
Dijk, J.D. van, et al.. (2021). Clinical value of machine learning-based interpretation of I-123 FP-CIT scans to detect Parkinson’s disease: a two-center study. Annals of Nuclear Medicine. 35(3). 378–385. 5 indexed citations
6.
Veen, Berlinda J. de Wit–van der, Henk G. van der Poel, Pim J. van Leeuwen, et al.. (2021). Cerenkov Luminescence Imaging in Prostate Cancer: Not the Only Light That Shines. Journal of Nuclear Medicine. 63(1). 29–35. 15 indexed citations
7.
Daemen, Jean H. T., et al.. (2021). The Automatic Quantification of Morphological Features of Pectus Excavatum Based on Three-Dimensional Images. Seminars in Thoracic and Cardiovascular Surgery. 34(2). 772–781. 12 indexed citations
8.
Slump, Cornelis H., et al.. (2019). Vessel wall enhancement of intracranial aneurysms: fact or artifact?. Neurosurgical FOCUS. 47(1). E18–E18. 34 indexed citations
9.
Berg, René van den, et al.. (2019). Intracranial aneurysm growth: consistency of morphological changes. Neurosurgical FOCUS. 47(1). E5–E5. 21 indexed citations
10.
Coolen, Bram F., et al.. (2019). Insufficient slow-flow suppression mimicking aneurysm wall enhancement in magnetic resonance vessel wall imaging: a phantom study. Neurosurgical FOCUS. 47(1). E19–E19. 33 indexed citations
11.
Vries, Evelien E. de, et al.. (2019). A Systematic Review for the Design of In Vitro Flow Studies of the Carotid Artery Bifurcation. Cardiovascular Engineering and Technology. 11(2). 111–127. 13 indexed citations
12.
Vries, Evelien E. de, Jason Voorneveld, Erik Groot Jebbink, et al.. (2018). In vitro high-frame-rate contrast-enhanced ultrasound particle image velocimetry in a carotid artery stent. Data Archiving and Networked Services (DANS). 5–5. 2 indexed citations
13.
Jansen, Ivo G.H., Wim H. van Zwam, Ido R. van den Wijngaard, et al.. (2017). Absence of Cortical Vein Opacification Is Associated with Lack of Intra-arterial Therapy Benefit in Stroke. Radiology. 286(2). 643–650. 54 indexed citations
14.
Boers, Anna M.M., Olvert A. Berkhemer, Cornelis H. Slump, et al.. (2016). Topographic distribution of cerebral infarct probability in patients with acute ischemic stroke: mapping of intra-arterial treatment effect. Journal of NeuroInterventional Surgery. 9(5). 431–436. 5 indexed citations
15.
Kant, Ilse, et al.. (2015). Low-dose CT angiography of the abdominal aorta and reduced contrast medium volume: Assessment of image quality and radiation dose. Clinical Radiology. 71(1). 64–73. 30 indexed citations
16.
Klein, Almar, et al.. (2009). Initial steps towards automatic segmentation of the wire frame of stent grafts in CT data. Data Archiving and Networked Services (DANS). 116–119. 3 indexed citations
17.
Druyvesteyn, W.F., et al.. (1998). Audibility of Nonlinear Distortion in Loudspeakers. Journal of the Audio Engineering Society. 1–22. 2 indexed citations
18.
Bree, Hans–Elias de, et al.. (1998). Comparison of Two Methods for Measurement of Horn Input Impedance. Journal of the Audio Engineering Society. 46(12). 1119–1125. 18 indexed citations
19.
Berkhoff, Arthur P., et al.. (1994). Modeling and Compensation of Nonlinear Distortion in Horn Loudspeakers. Journal of the Audio Engineering Society. 43(718). 592–598. 7 indexed citations
20.
Slump, Cornelis H., et al.. (1994). Reduction of Nonlinear Distortion in Loudspeakers with Digital Motional feedback. Journal of the Audio Engineering Society. 7 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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