J.J. Bluemink

1.0k total citations
19 papers, 376 citations indexed

About

J.J. Bluemink is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, J.J. Bluemink has authored 19 papers receiving a total of 376 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Radiation and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in J.J. Bluemink's work include Advanced MRI Techniques and Applications (7 papers), Advanced Radiotherapy Techniques (6 papers) and Particle Dynamics in Fluid Flows (5 papers). J.J. Bluemink is often cited by papers focused on Advanced MRI Techniques and Applications (7 papers), Advanced Radiotherapy Techniques (6 papers) and Particle Dynamics in Fluid Flows (5 papers). J.J. Bluemink collaborates with scholars based in Netherlands, United States and Germany. J.J. Bluemink's co-authors include Detlef Lohse, Andréa Prosperetti, L. van Wijngaarden, J J W Lagendijk, J. Wolthaus, Peter R. Luijten, Bram van Asselen, Bas W. Raaymakers, S. Hackett and Jacques Magnaudet and has published in prestigious journals such as Journal of Fluid Mechanics, Magnetic Resonance in Medicine and Physics in Medicine and Biology.

In The Last Decade

J.J. Bluemink

18 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J.J. Bluemink Netherlands	11	170	133	128	111	95	19	376
B. Dörschel Germany	15	148 0.9×	504 3.8×	205 1.6×	55 0.5×	34 0.4×	46	691
Edward Waller Canada	8	59 0.3×	172 1.3×	48 0.4×	11 0.1×	32 0.3×	44	310
Seyyed Hashem Miri Hakimabad Iran	12	212 1.2×	316 2.4×	154 1.2×	8 0.1×	84 0.9×	77	482
V. Peyrés Spain	12	58 0.3×	185 1.4×	22 0.2×	39 0.4×	30 0.3×	39	365
E. Gargioni Germany	14	83 0.5×	239 1.8×	264 2.1×	51 0.5×	41 0.4×	47	503
N. Robert Bennett United States	11	429 2.5×	115 0.9×	118 0.9×	20 0.2×	412 4.3×	30	518
R. Graumann Germany	10	262 1.5×	64 0.5×	22 0.2×	19 0.2×	176 1.9×	21	409
M. Kurano Japan	15	78 0.5×	321 2.4×	235 1.8×	50 0.5×	18 0.2×	28	475
T. Minniti United Kingdom	13	39 0.2×	278 2.1×	15 0.1×	23 0.2×	35 0.4×	38	376
Jörgen Olofsson Sweden	12	177 1.0×	246 1.8×	186 1.5×	165 1.5×	57 0.6×	21	476

Countries citing papers authored by J.J. Bluemink

Since Specialization

Citations

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

Fields of papers citing papers by J.J. Bluemink

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J.J. Bluemink

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Sangen, Maurice J.C. van der, et al.. (2024). Comparison of the use of a clinically implemented deep learning segmentation model with the simulated study setting for breast cancer patients receiving radiotherapy. Acta Oncologica. 63. 477–481. 2 indexed citations

Theuws, Jacqueline, et al.. (2023). Evaluation of a clinically introduced deep learning model for radiotherapy treatment planning of breast cancer. Physics and Imaging in Radiation Oncology. 28. 100496–100496. 5 indexed citations

Rijkaart, Dorien, et al.. (2023). Clinical evaluation of a deep learning segmentation model including manual adjustments afterwards for locally advanced breast cancer. Technical Innovations & Patient Support in Radiation Oncology. 26. 100211–100211. 10 indexed citations

Woodings, S., S. Hackett, Bram van Asselen, et al.. (2021). Acceptance procedure for the linear accelerator component of the 1.5 T MRI‐linac. Journal of Applied Clinical Medical Physics. 22(8). 45–59. 20 indexed citations

Woodings, S., J.J. Bluemink, Yury Niatsetski, et al.. (2018). Beam characterisation of the 1.5 T MRI-linac. Physics in Medicine and Biology. 63(8). 85015–85015. 59 indexed citations

Hackett, S., Bram van Asselen, J. Wolthaus, et al.. (2018). Spiraling contaminant electrons increase doses to surfaces outside the photon beam of an MRI-linac with a perpendicular magnetic field. Physics in Medicine and Biology. 63(9). 95001–95001. 41 indexed citations

Egmond, Sylvia L. van, Inge Stegeman, Frank A. Pameijer, et al.. (2018). Systematic review of the diagnostic value of magnetic resonance imaging for early glottic carcinoma. Laryngoscope Investigative Otolaryngology. 3(1). 49–55. 4 indexed citations

Tijssen, Rob H.N., S.P.M. Crijns, J.J. Bluemink, et al.. (2017). OC-0257: Comprehensive MRI Acceptance Testing & Commissioning of a 1.5T MR-Linac: Guidelines and Results. Radiotherapy and Oncology. 123. S130–S131. 5 indexed citations

Henning, A, Alexander Fuchs, Alexander Raaijmakers, et al.. (2016). ¹H MRS in the human spinal cord at 7 T using a dielectric waveguide transmitter, RF shimming and a high density receive array. NMR in Biomedicine. 29(9). 1231–1239. 10 indexed citations

10.

Bluemink, J.J., Alexander Raaijmakers, Anna Andreychenko, et al.. (2015). Dielectric waveguides for ultrahigh field magnetic resonance imaging. Magnetic Resonance in Medicine. 76(4). 1314–1324. 6 indexed citations

11.

Bluemink, J.J., et al.. (2014). MRI of the carotid artery at 7 Tesla: Quantitative comparison with 3 Tesla. Journal of Magnetic Resonance Imaging. 41(3). 773–780. 27 indexed citations

12.

Bluemink, J.J., Alexander Raaijmakers, Anna Andreychenko, et al.. (2012). High‐resolution MRI of the carotid arteries using a leaky waveguide transmitter and a high‐density receive array at 7 T. Magnetic Resonance in Medicine. 69(4). 1186–1193. 28 indexed citations

13.

Berg, Cornelis A. T. van den, J.J. Bluemink, Astrid L.H.M.W. van Lier, et al.. (2012). MR and hyperthermia: Exploiting similarities for mutual benefit. 632–635. 3 indexed citations

14.

Andreychenko, Anna, J.J. Bluemink, Alexander Raaijmakers, et al.. (2012). Improved RF performance of travelling wave MR with a high permittivity dielectric lining of the bore. Magnetic Resonance in Medicine. 70(3). 885–894. 17 indexed citations

15.

Bluemink, J.J., Detlef Lohse, Andréa Prosperetti, & L. van Wijngaarden. (2009). Drag and lift forces on particles in a rotating flow. Journal of Fluid Mechanics. 643. 1–31. 37 indexed citations

16.

Bluemink, J.J., Detlef Lohse, Andréa Prosperetti, & L. van Wijngaarden. (2008). A sphere in a uniformly rotating or shearing flow. Journal of Fluid Mechanics. 600. 201–233. 38 indexed citations

17.

Nierop, Ernst A. van, Stefan Luther, J.J. Bluemink, et al.. (2007). Drag and lift forces on bubbles in a rotating flow. Journal of Fluid Mechanics. 571. 439–454. 55 indexed citations

18.

Bluemink, J.J., Aurore Naso, & Andréa Prosperetti. (2006). The Physalis method for particle simulations. University of Twente Research Information.

19.

Bluemink, J.J., Ernst A. van Nierop, Stefan Luther, et al.. (2005). Asymmetry-induced particle drift in a rotating flow. Physics of Fluids. 17(7). 9 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.

Explore authors with similar magnitude of impact