Gregor Urban

2.5k total citations · 2 hit papers
24 papers, 1.6k citations indexed

About

Gregor Urban is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Gregor Urban has authored 24 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Molecular Biology and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Gregor Urban's work include Protein Structure and Dynamics (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Machine Learning in Materials Science (3 papers). Gregor Urban is often cited by papers focused on Protein Structure and Dynamics (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Machine Learning in Materials Science (3 papers). Gregor Urban collaborates with scholars based in United States, Germany and Ireland. Gregor Urban's co-authors include Pierre Baldi, Martin Bendszus, Jens Kleesiek, Talal Alkayali, William E. Karnes, Mohit Mittal, Priyam Tripathi, Farid Jalali, Dániel Schwarz and Armin Biller and has published in prestigious journals such as Bioinformatics, Gastroenterology and NeuroImage.

In The Last Decade

Gregor Urban

23 papers receiving 1.5k citations

Hit Papers

Deep Learning Localizes and Identifies Polyps in Real Tim... 2016 2026 2019 2022 2018 2016 100 200 300 400
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.

  1. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy
    2018 494 citations Gregor Urban, Priyam Tripathi et al. Gastroenterology profile →
  2. Deep MRI brain extraction: A 3D convolutional neural network for skull stripping
    2016 331 citations Jens Kleesiek, Gregor Urban et al. NeuroImage profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gregor Urban United States 12 454 398 381 367 240 24 1.6k
Chung‐Ming Chen Taiwan 24 1.1k 2.4× 452 1.1× 652 1.7× 388 1.1× 72 0.3× 127 2.5k
Yi Gao China 21 764 1.7× 626 1.6× 845 2.2× 274 0.7× 95 0.4× 109 2.1k
Jens Kleesiek Germany 21 994 2.2× 501 1.3× 503 1.3× 171 0.5× 436 1.8× 107 2.3k
Xiao Han China 25 660 1.5× 350 0.9× 738 1.9× 251 0.7× 102 0.4× 145 1.9k
Atam P. Dhawan United States 24 650 1.4× 712 1.8× 554 1.5× 325 0.9× 81 0.3× 128 2.0k
Frank G. Zöllner Germany 25 1.5k 3.3× 375 0.9× 412 1.1× 140 0.4× 124 0.5× 138 2.2k
Benzheng Wei China 17 1.1k 2.3× 727 1.8× 853 2.2× 83 0.2× 163 0.7× 74 1.9k
Wei Shao China 24 528 1.2× 270 0.7× 547 1.4× 136 0.4× 184 0.8× 105 1.8k
Dahong Qian China 21 664 1.5× 259 0.7× 221 0.6× 69 0.2× 34 0.1× 61 1.3k

Countries citing papers authored by Gregor Urban

Since Specialization
Citations

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

Fields of papers citing papers by Gregor Urban

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gregor Urban

This figure shows the co-authorship network connecting the top 25 collaborators of Gregor Urban. A scholar is included among the top collaborators of Gregor Urban 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 Gregor Urban. Gregor Urban 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.
Chen, Siwei, Gregor Urban, & Pierre Baldi. (2022). Weakly Supervised Polyp Segmentation in Colonoscopy Images Using Deep Neural Networks. Journal of Imaging. 8(5). 121–121. 8 indexed citations
2.
Lin, Ken, et al.. (2021). Accurate Identification of the Trabecular Meshwork under Gonioscopic View in Real Time Using Deep Learning. Ophthalmology Glaucoma. 5(4). 402–412. 7 indexed citations
3.
Urban, Gregor, et al.. (2020). Combining Deep Learning With Optical Coherence Tomography Imaging to Determine Scalp Hair and Follicle Counts. Lasers in Surgery and Medicine. 53(1). 171–178. 14 indexed citations
4.
Urban, Gregor, Mirko Torrisi, Chr̀istophe Magnan, Gianluca Pollastri, & Pierre Baldi. (2020). Protein profiles: Biases and protocols. Computational and Structural Biotechnology Journal. 18. 2281–2289. 8 indexed citations
5.
Urban, Gregor, et al.. (2020). Classifying shoulder implants in X-ray images using deep learning. Computational and Structural Biotechnology Journal. 18. 967–972. 39 indexed citations
6.
Lee, Christine K., Christopher Wray, Vatche G. Agopian, et al.. (2020). Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data. Transplantation Proceedings. 52(1). 246–258. 44 indexed citations
7.
Urban, Gregor, Priyam Tripathi, Talal Alkayali, et al.. (2018). Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy. Gastroenterology. 155(4). 1069–1078.e8. 494 indexed citations breakdown →
8.
Urban, Gregor, Niranjan Subrahmanya, & Pierre Baldi. (2018). Inner and Outer Recursive Neural Networks for Chemoinformatics Applications. Journal of Chemical Information and Modeling. 58(2). 207–211. 15 indexed citations
9.
Tripathi, Priyam, Gregor Urban, Talal Alkayali, et al.. (2018). 133 - Computer-Assisted Polyp Detection Identifies all Polyps Found by Expert Colonoscopists – And then Some. Gastroenterology. 154(6). S–36. 3 indexed citations
10.
Dorkenwald, Sven, et al.. (2017). Automated synaptic connectivity inference for volume electron microscopy. Nature Methods. 14(4). 435–442. 74 indexed citations
11.
Fooshee, David, Eugene S. Gutman, Gregor Urban, et al.. (2017). Deep learning for chemical reaction prediction. Molecular Systems Design & Engineering. 3(3). 442–452. 148 indexed citations
12.
Karnes, William E., Talal Alkayali, Mohit Mittal, et al.. (2017). Su1642 Automated Polyp Detection Using Deep Learning: Leveling the Field. Gastrointestinal Endoscopy. 85(5). AB376–AB377. 9 indexed citations
13.
Wang, Shengjie, Abdelrahman Mohamed, Rich Caruana, et al.. (2016). Analysis of Deep Neural Networks with Extended Data Jacobian Matrix. International Conference on Machine Learning. 718–726. 8 indexed citations
14.
Kleesiek, Jens, Gregor Urban, Alexander Hubert, et al.. (2016). Deep MRI brain extraction: A 3D convolutional neural network for skull stripping. NeuroImage. 129. 460–469. 331 indexed citations breakdown →
15.
Guest, Daniel, et al.. (2016). Jet flavor classification in high-energy physics with deep neural networks. Physical review. D. 94(11). 99 indexed citations
16.
Geras, Krzysztof J., Abdelrahman Mohamed, Rich Caruana, et al.. (2015). Compressing LSTMs into CNNs.. arXiv (Cornell University). 3 indexed citations
17.
Urban, Gregor, Martin Bendszus, Fred A. Hamprecht, & Jens Kleesiek. (2014). Multi-modal Brain Tumor Segmentation using Deep Convolutional Neural Networks. 111 indexed citations
18.
19.
Urban, Gregor, et al.. (1964). Training a computer to assign descriptors to documents. 563–563. 3 indexed citations
20.
Kirsch, Russell A., et al.. (1958). Experiments in processing pictorial information with a digital computer. 221–229. 73 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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