Wouter Bulten

1.6k total citations · 2 hit papers
9 papers, 998 citations indexed

About

Wouter Bulten is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Wouter Bulten has authored 9 papers receiving a total of 998 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Pulmonary and Respiratory Medicine, 7 papers in Artificial Intelligence and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Wouter Bulten's work include Prostate Cancer Diagnosis and Treatment (7 papers), AI in cancer detection (7 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Wouter Bulten is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (7 papers), AI in cancer detection (7 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Wouter Bulten collaborates with scholars based in Netherlands, Sweden and Australia. Wouter Bulten's co-authors include Geert Litjens, Jeroen van der Laak, Bram van Ginneken, Hans Pinckaers, Christina Hulsbergen‐van de Kaa, Hester van Boven, Robert Vink, Péter Bándi, Thomas de Bel and John‐Melle Bokhorst and has published in prestigious journals such as Scientific Reports, The Lancet Oncology and Medical Image Analysis.

In The Last Decade

Wouter Bulten

9 papers receiving 985 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.

Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study

2020 421 citations Wouter Bulten, Hans Pinckaers et al. The Lancet Oncology profile →
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology

2019 317 citations David Tellez, Geert Litjens et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wouter Bulten Netherlands	8	752	530	275	210	157	9	998
Thomas de Bel Netherlands	10	641 0.9×	459 0.9×	231 0.8×	245 1.2×	159 1.0×	16	1.0k
Hans Pinckaers Netherlands	12	608 0.8×	477 0.9×	183 0.7×	217 1.0×	150 1.0×	20	899
Meyke Hermsen Netherlands	13	1.1k 1.4×	734 1.4×	428 1.6×	227 1.1×	225 1.4×	22	1.6k
Robert MacDonald Australia	6	517 0.7×	429 0.8×	147 0.5×	254 1.2×	159 1.0×	15	986
N. K. Timofeeva Netherlands	4	717 1.0×	471 0.9×	292 1.1×	106 0.5×	137 0.9×	10	963
Luke Geneslaw United States	4	1.1k 1.5×	773 1.5×	401 1.5×	164 0.8×	340 2.2×	4	1.5k
Alexi Baidoshvili Netherlands	15	492 0.7×	346 0.7×	193 0.7×	89 0.4×	149 0.9×	22	920
Maschenka Balkenhol Netherlands	13	685 0.9×	530 1.0×	298 1.1×	63 0.3×	151 1.0×	21	906
Norman Zerbe Germany	12	501 0.7×	314 0.6×	194 0.7×	88 0.4×	118 0.8×	34	780
Guillaume Jaume United States	11	577 0.8×	401 0.8×	210 0.8×	67 0.3×	114 0.7×	14	885

Countries citing papers authored by Wouter Bulten

Since Specialization

Citations

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

Fields of papers citing papers by Wouter Bulten

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wouter Bulten

This figure shows the co-authorship network connecting the top 25 collaborators of Wouter Bulten. A scholar is included among the top collaborators of Wouter Bulten 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 Wouter Bulten. Wouter Bulten 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:

9 of 9 papers shown

1.

Kartasalo, Kimmo, Wouter Bulten, Brett Delahunt, et al.. (2021). Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies—Current Status and Next Steps. European Urology Focus. 7(4). 687–691. 31 indexed citations

2.

Bulten, Wouter, Hans Pinckaers, Hester van Boven, et al.. (2020). Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study. arXiv (Cornell University). 77 indexed citations

3.

Bulten, Wouter, Geert Litjens, Hans Pinckaers, et al.. (2020). The PANDA challenge: Prostate cANcer graDe Assessment using the Gleason grading system. Zenodo (CERN European Organization for Nuclear Research). 14 indexed citations

4.

Bulten, Wouter, Hans Pinckaers, Hester van Boven, et al.. (2020). Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study. The Lancet Oncology. 21(2). 233–241. 421 indexed citations breakdown →

5.

Bulten, Wouter, Péter Bándi, Rob van de Loo, et al.. (2019). Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard. Scientific Reports. 9(1). 864–864. 101 indexed citations

6.

Tellez, David, Geert Litjens, Péter Bándi, et al.. (2019). Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. Medical Image Analysis. 58. 101544–101544. 317 indexed citations breakdown →

7.

Pinckaers, Hans, Wouter Bulten, & Geert Litjens. (2019). High resolution whole prostate biopsy classification using streaming stochastic gradient descent. 8–8. 1 indexed citations

8.

Bulten, Wouter, Geert Litjens, Christina A. Hulsbergen‐van de Kaa, & Jeroen van der Laak. (2018). Automated segmentation of epithelial tissue in prostatectomy slides using deep learning. 27–27. 12 indexed citations

9.

Bulten, Wouter, et al.. (2016). Human SLAM, Indoor Localisation of Devices and Users. Radboud Repository (Radboud University). 211–222. 24 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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