Günter Schmidt

679 total citations
28 papers, 420 citations indexed

About

Günter Schmidt is a scholar working on Artificial Intelligence, Oncology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Günter Schmidt has authored 28 papers receiving a total of 420 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 9 papers in Oncology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Günter Schmidt's work include AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Cancer Immunotherapy and Biomarkers (6 papers). Günter Schmidt is often cited by papers focused on AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Cancer Immunotherapy and Biomarkers (6 papers). Günter Schmidt collaborates with scholars based in United Kingdom, Germany and Spain. Günter Schmidt's co-authors include Nicolas Brieu, G. Binnig, Armin Meier, David J. Harrison, Peter D. Caie, Maria Athelogou, Katharina Nekolla, Ines P. Nearchou, Angela Platt‐Higgins and Barry R. Davies and has published in prestigious journals such as Cancer Research, Scientific Reports and American Journal Of Pathology.

In The Last Decade

Günter Schmidt

27 papers receiving 403 citations

Peers

Günter Schmidt

RNMI

ONCOL

CVPR

Tokiya Abe Japan

Daniel Heim Germany

Anna Korzyńska Poland

Nick Weiss Germany

Vipul Baxi United States

Quirine F. Manson Netherlands

Xiaotao Yin China

Żaneta Świderska-Chadaj Poland

Can Koyuncu United States

Caixia Dong China

Tokiya Abe Japan

Günter Schmidt

89 ×0.6

RNMI

176 ×1.3

ONCOL

150 ×1.3

CVPR

166 ×1.5

35 ×0.6

Citations per year, relative to Günter Schmidt Günter Schmidt (= 1×) peers Tokiya Abe

Countries citing papers authored by Günter Schmidt

Since Specialization

Citations

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

Fields of papers citing papers by Günter Schmidt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Günter Schmidt

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

All Works

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20 of 20 papers shown

Brieu, Nicolas, Ines P. Nearchou, Ognjen Arandjelović, et al.. (2021). Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning. Cancers. 13(7). 1624–1624. 19 indexed citations

Meier, Armin, Keith E. Steele, Marlon C. Rebelatto, et al.. (2021). Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images. IEEE Transactions on Medical Imaging. 40(9). 2513–2523. 22 indexed citations

Meier, Armin, et al.. (2021). Breast cancer patient stratification using domain adaptation based lymphocyte detection in HER2 stained tissue sections. 2 indexed citations

Meier, Armin, Katharina Nekolla, Lindsay C. Hewitt, et al.. (2020). Hypothesis‐free deep survival learning applied to the tumour microenvironment in gastric cancer. The Journal of Pathology Clinical Research. 6(4). 273–282. 26 indexed citations

Harder, Nathalie, Ralf Schönmeyer, Katharina Nekolla, et al.. (2019). Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma. Scientific Reports. 9(1). 7449–7449. 43 indexed citations

Brieu, Nicolas, et al.. (2019). Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis. Scientific Reports. 9(1). 5174–5174. 34 indexed citations

Harder, Nathalie, Maria Athelogou, Harald Hessel, et al.. (2018). Tissue Phenomics for prognostic biomarker discovery in low- and intermediate-risk prostate cancer. Scientific Reports. 8(1). 4470–4470. 21 indexed citations

Brieu, Nicolas, et al.. (2018). Augmenting TNM staging with machine learning-based immune profiling for improved prognosis prediction in muscle-invasive bladder cancer patients. Annals of Oncology. 29. viii28–viii29. 3 indexed citations

Schmidt, Günter, et al.. (2017). Hierarchical patch-based co-registration of differently stained histopathology slides. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10140. 1014009–1014009. 6 indexed citations

10.

Brieu, Nicolas & Günter Schmidt. (2017). Learning size adaptive local maxima selection for robust nuclei detection in histopathology images. 33. 937–941. 11 indexed citations

11.

Schmidt, Günter, Ingolf Juhasz‐Böss, Erich‐Franz Solomayer, & Daniel J. Herr. (2014). Electrochemotherapy in Breast Cancer: A Review of References. Geburtshilfe und Frauenheilkunde. 74(6). 557–562. 29 indexed citations

12.

Schönmeyer, Ralf, et al.. (2010). Cognition Network Technology prototype of a CAD system for mammography to assist radiologists by finding similar cases in a reference database. International Journal of Computer Assisted Radiology and Surgery. 6(1). 127–134. 12 indexed citations

13.

Schmidt, Günter, Maria Athelogou, R Korn, & G. Binnig. (2007). Cognition Network Technology for a Fully Automated 3D Segmentation of Liver. 22 indexed citations

14.

Schmidt, Günter, et al.. (2003). A comparative review of digital image stabilising algorithms for mobile video communications. 17. 88–89. 5 indexed citations

15.

Schmidt, Günter, et al.. (2002). Effects of Combined Therapy With Clopidogrel and Acetylsalicylic Acid on Platelet Glycoprotein Expression and Aggregation. Journal of Cardiovascular Pharmacology. 39(4). 523–532. 13 indexed citations

16.

Binnig, G., et al.. (2002). Win machines start to think like humans?. Europhysics news. 33(2). 44–47. 9 indexed citations

17.

Binnig, G., et al.. (2000). Handling Complexity with Self-Organizing Fractial Semantic Networks. 2(4). 151–162. 4 indexed citations

18.

Davies, Barry R., Angela Platt‐Higgins, Günter Schmidt, & Philip S. Rudland. (1999). Development of Hyperplasias, Preneoplasias, and Mammary Tumors in MMTV-c-erbB-2 and MMTV-TGFα Transgenic Rats. American Journal Of Pathology. 155(1). 303–314. 27 indexed citations

19.

Schmidt, Günter, et al.. (1999). A comparative review of digital image stabilising algorithms for mobile video communications. IEEE Transactions on Consumer Electronics. 45(3). 591–597. 59 indexed citations

20.

House, Donald H., et al.. (1998). Visualizing a real forest. IEEE Computer Graphics and Applications. 18(1). 12–15. 12 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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