Markus D. Herrmann

2.1k total citations
26 papers, 473 citations indexed

About

Markus D. Herrmann is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Biophysics. According to data from OpenAlex, Markus D. Herrmann has authored 26 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Biophysics. Recurrent topics in Markus D. Herrmann's work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Cell Image Analysis Techniques (5 papers). Markus D. Herrmann is often cited by papers focused on AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Cell Image Analysis Techniques (5 papers). Markus D. Herrmann collaborates with scholars based in United States, Germany and United Kingdom. Markus D. Herrmann's co-authors include Lucas Pelkmans, Gabriele Gut, Jochen K. Lennerz, Nico Battich, Thomas Stoeger, Peter Möller, Stephanie E. Weissinger, David Clunie, Andriy Fedorov and Ron Kikinis and has published in prestigious journals such as Science, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Markus D. Herrmann

24 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus D. Herrmann United States 9 301 147 63 60 57 26 473
Thierry Pécot United States 13 262 0.9× 67 0.5× 29 0.5× 63 1.1× 67 1.2× 34 502
Heba Sailem United Kingdom 12 307 1.0× 259 1.8× 107 1.7× 53 0.9× 48 0.8× 26 662
Benjamin Glass United States 9 210 0.7× 122 0.8× 55 0.9× 66 1.1× 59 1.0× 25 534
Mar Arias-García United Kingdom 7 148 0.5× 99 0.7× 52 0.8× 30 0.5× 28 0.5× 13 337
Marcus Bode Germany 10 393 1.3× 222 1.5× 31 0.5× 47 0.8× 18 0.3× 13 560
Manuela Friedenberger Germany 7 336 1.1× 210 1.4× 26 0.4× 32 0.5× 18 0.3× 8 489
Zhan Zhang China 16 544 1.8× 36 0.2× 69 1.1× 51 0.8× 29 0.5× 24 793
Gerald Fontenay United States 10 288 1.0× 56 0.4× 25 0.4× 34 0.6× 77 1.4× 17 479
Ashley Kiemen United States 9 98 0.3× 51 0.3× 35 0.6× 33 0.6× 45 0.8× 23 270
Patrick Warnat Germany 8 581 1.9× 132 0.9× 23 0.4× 19 0.3× 37 0.6× 11 852

Countries citing papers authored by Markus D. Herrmann

Since Specialization
Citations

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

Fields of papers citing papers by Markus D. Herrmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus D. Herrmann. 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 Markus D. Herrmann. The network helps show where Markus D. Herrmann may publish in the future.

Co-authorship network of co-authors of Markus D. Herrmann

This figure shows the co-authorship network connecting the top 25 collaborators of Markus D. Herrmann. A scholar is included among the top collaborators of Markus D. Herrmann 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 Markus D. Herrmann. Markus D. Herrmann 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.
Yüce, Anıl, Christian Doerig, Agata Mosinska, et al.. (2024). Deep Learning Predicts Risk of Large B-Cell Lymphoma Progression upon R-CHOP Therapy from Baseline Histology. Blood. 144(Supplement 1). 108–108.
2.
Pieper, Steven, William J.R. Longabaugh, David Clunie, et al.. (2023). Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology. Nature Communications. 14(1). 1572–1572. 19 indexed citations
3.
Herrmann, Markus D., David Clunie, William Kingdon Clifford, et al.. (2023). The NCI Imaging Data Commons as a platform for reproducible research in computational pathology. Computer Methods and Programs in Biomedicine. 242. 107839–107839. 5 indexed citations
4.
Li, Annie, Julia Thierauf, Atul K. Bhan, et al.. (2023). 102 Immune landscape of adenoid cystic carcinoma using multiplex immunofluorescence and digital pathology. SHILAP Revista de lepidopterología. A116–A116. 1 indexed citations
5.
Bridge, Christopher P., Steven C. Pieper, Jochen K. Lennerz, et al.. (2022). Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology. Journal of Digital Imaging. 35(6). 1719–1737. 9 indexed citations
6.
Papazoglou, Αndreas S., Efstratios Karagiannidis, Dimitrios V. Moysidis, et al.. (2022). Volumetric Tissue Imaging of Surgical Tissue Specimens Using Micro–Computed Tomography: An Emerging Digital Pathology Modality for Nondestructive, Slide-Free Microscopy—Clinical Applications of Digital Pathology in 3 Dimensions. American Journal of Clinical Pathology. 159(3). 242–254. 3 indexed citations
7.
Dash, Rajesh, et al.. (2021). Integrating the Health-care Enterprise Pathology and Laboratory Medicine Guideline for Digital Pathology Interoperability. Journal of Pathology Informatics. 12(1). 16–16. 10 indexed citations
8.
Papazoglou, Αndreas S., Efstratios Karagiannidis, Dimitrios V. Moysidis, et al.. (2021). Current clinical applications and potential perspective of micro-computed tomography in cardiovascular imaging: A systematic scoping review. Hellenic Journal of Cardiology. 62(6). 399–407. 17 indexed citations
9.
Fedorov, Andriy, William J.R. Longabaugh, David Pot, et al.. (2021). NCI Imaging Data Commons. International Journal of Radiation Oncology*Biology*Physics. 111(3). e101–e101. 2 indexed citations
10.
Marble, Hetal D., Sarah Dudgeon, Amanda Lowe, et al.. (2020). A Regulatory Science Initiative to Harmonize and Standardize Digital Pathology and Machine Learning Processes to Speed up Clinical Innovation to Patients. Journal of Pathology Informatics. 11(1). 22–22. 21 indexed citations
11.
Herrmann, Markus D. & Jochen K. Lennerz. (2020). Technische, operative und regulatorische Aspekte für die Nutzung der digitalen und rechnergestützten Pathologie. Der Pathologe. 41(S2). 103–110. 1 indexed citations
12.
Herrmann, Markus D., et al.. (2019). Research Data Management in the Lab. PUB – Publications at Bielefeld University (Bielefeld University).
13.
Gut, Gabriele, Markus D. Herrmann, & Lucas Pelkmans. (2018). Multiplexed protein maps link subcellular organization to cellular states. Science. 361(6401). 297 indexed citations
14.
Herrmann, Markus D., et al.. (2018). Blockchain-backed analytics. Adding blockchain-based quality gates to data science projects.. RiuNet (Politechnical University of Valencia). 3 indexed citations
15.
Herrmann, Markus D., et al.. (2016). A MAP estimator based on geometric Brownian motion for sample distances of laser triangulation data. Optics and Lasers in Engineering. 86. 98–105. 4 indexed citations
16.
Stoeger, Thomas, et al.. (2015). Computer vision for image-based transcriptomics. Methods. 85. 44–53. 25 indexed citations
17.
Herrmann, Markus D., Andreas Essig, Jochen Spieß, et al.. (2014). Isolated Whipple's Endocarditis: An Underestimated Diagnosis That Requires Molecular Analysis of Surgical Material. The Annals of Thoracic Surgery. 98(1). e1–e3. 7 indexed citations
18.
Weissinger, Stephanie E., et al.. (2014). A nuclear circularity-based classifier for diagnostic distinction of desmoplastic from spindle cell melanoma in digitized histological images. Journal of Pathology Informatics. 5(1). 40–40. 21 indexed citations
19.
Herrmann, Markus D., Jochen K. Lennerz, Lars Bullinger, et al.. (2013). Transitory dasatinib-resistant states in KITmut t(8;21) acute myeloid leukemia cells correlate with altered KIT expression. Experimental Hematology. 42(2). 90–100. 9 indexed citations
20.
Kunz, R., Jens Mayer, Biruta Witte, & Markus D. Herrmann. (1996). Topographic anatomic aspects of laparoscopic hernia repair. Der Chirurg. 67(8). 807–813. 1 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

Breakdown of academic impact, for papers by Thierry Pécot Breakdown of academic impact, for papers by Heba Sailem Breakdown of academic impact, for papers by Benjamin Glass Breakdown of academic impact, for papers by Mar Arias-García Breakdown of academic impact, for papers by Marcus Bode Breakdown of academic impact, for papers by Manuela Friedenberger Breakdown of academic impact, for papers by Zhan Zhang Breakdown of academic impact, for papers by Gerald Fontenay Breakdown of academic impact, for papers by Ashley Kiemen Breakdown of academic impact, for papers by Patrick Warnat
Rankless by CCL
2026