Ralf Schönmeyer

718 total citations
16 papers, 544 citations indexed

About

Ralf Schönmeyer is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ralf Schönmeyer has authored 16 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ralf Schönmeyer's work include Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (3 papers) and Functional Brain Connectivity Studies (3 papers). Ralf Schönmeyer is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (3 papers) and Functional Brain Connectivity Studies (3 papers). Ralf Schönmeyer collaborates with scholars based in Germany, France and United Kingdom. Ralf Schönmeyer's co-authors include Corinna Haenschel, David E.J. Linden, Anna Rotarska-Jagiela, Viola Oertel, Kai Vogeley, Vincent van de Ven, Christian Knöchel, Peter J. Uhlhaas, Johannes Pantel and David Prvulovic and has published in prestigious journals such as Journal of Neuroscience, NeuroImage and Scientific Reports.

In The Last Decade

Ralf Schönmeyer

16 papers receiving 538 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ralf Schönmeyer Germany 11 270 258 115 68 57 16 544
Ahmed Radwan Belgium 14 131 0.5× 90 0.3× 103 0.9× 62 0.9× 70 1.2× 47 539
Ben A. Duffy United States 17 156 0.6× 222 0.9× 74 0.6× 39 0.6× 49 0.9× 26 655
Ilwoo Lyu United States 16 353 1.3× 220 0.9× 66 0.6× 53 0.8× 51 0.9× 54 596
Ani Eloyan United States 14 190 0.7× 444 1.7× 189 1.6× 33 0.5× 20 0.4× 42 761
Jia Guo United States 15 221 0.8× 119 0.5× 71 0.6× 53 0.8× 14 0.2× 55 613
María de la Iglesia-Vayá Spain 13 393 1.5× 173 0.7× 72 0.6× 244 3.6× 16 0.3× 47 867
Jan Freyberg United States 8 214 0.8× 289 1.1× 63 0.5× 230 3.4× 15 0.3× 11 741
Claudio Stamile France 13 189 0.7× 88 0.3× 40 0.3× 63 0.9× 44 0.8× 27 488
Camilo Bermudez United States 13 262 1.0× 105 0.4× 79 0.7× 112 1.6× 44 0.8× 29 594
Eva Janoušová Czechia 12 80 0.3× 180 0.7× 69 0.6× 82 1.2× 19 0.3× 31 568

Countries citing papers authored by Ralf Schönmeyer

Since Specialization
Citations

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

Fields of papers citing papers by Ralf Schönmeyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ralf Schönmeyer

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

All Works

16 of 16 papers shown
1.
Schönmeyer, Ralf, Germain Forestier, Nicolas Brieu, et al.. (2020). Graph-based description of tertiary lymphoid organs at single-cell level. PLoS Computational Biology. 16(2). e1007385–e1007385. 7 indexed citations
2.
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
3.
Alfonso, Juan Carlos López, Ralf Schönmeyer, Anne Grote, et al.. (2017). Image analysis of immune cell patterns in the human mammary gland during the menstrual cycle refines lymphocytic lobulitis. Breast Cancer Research and Treatment. 164(2). 305–315. 3 indexed citations
4.
Andrés, Christian, R. Hein, Tilo Biedermann, et al.. (2017). iDermatoPath – a novel software tool for mitosis detection in H&E‐stained tissue sections of malignant melanoma. Journal of the European Academy of Dermatology and Venereology. 31(7). 1137–1147. 11 indexed citations
5.
Alfonso, Juan Carlos López, Ralf Schönmeyer, Nicolas Brieu, et al.. (2016). In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium. Scientific Reports. 6(1). 33322–33322. 21 indexed citations
6.
Naegel, Benoît, Germain Forestier, Ralf Schönmeyer, et al.. (2016). Detection of lobular structures in normal breast tissue. Computers in Biology and Medicine. 74. 91–102. 16 indexed citations
7.
Harder, Nathalie, Maria Athelogou, Harald Hessel, et al.. (2016). Co-occurrence features characterizing gland distribution patterns as new prognostic markers in prostate cancer whole-slide images. 9420. 807–810. 3 indexed citations
8.
Knöchel, Christian, Viola Oertel‐Knöchel, Ralf Schönmeyer, et al.. (2011). Interhemispheric hypoconnectivity in schizophrenia: Fiber integrity and volume differences of the corpus callosum in patients and unaffected relatives. NeuroImage. 59(2). 926–934. 91 indexed citations
9.
Oertel, Viola, Christian Knöchel, Anna Rotarska-Jagiela, et al.. (2010). Reduced Laterality as a Trait Marker ofSchizophrenia—Evidence from Structural and Functional Neuroimaging. Journal of Neuroscience. 30(6). 2289–2299. 111 indexed citations
10.
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
11.
Schönmeyer, Ralf, et al.. (2009). Mild Cognitive Impairment in the Elderly is Associated with Volume Loss of the Cholinergic Basal Forebrain Region. Biological Psychiatry. 67(6). 588–591. 47 indexed citations
12.
Athelogou, Maria, et al.. (2008). Fully Automated 3D Segmentation of Liver. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 180(S 1). 11 indexed citations
13.
Rotarska-Jagiela, Anna, Ralf Schönmeyer, Viola Oertel, et al.. (2007). The corpus callosum in schizophrenia-volume and connectivity changes affect specific regions. NeuroImage. 39(4). 1522–1532. 132 indexed citations
14.
Schönmeyer, Ralf, David Prvulovic, Anna Rotarska-Jagiela, Corinna Haenschel, & David E.J. Linden. (2006). Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology. Magnetic Resonance Imaging. 24(10). 1377–1387. 26 indexed citations
15.
Schönmeyer, Ralf, et al.. (2003). On-chip template training for pattern matching by cellular neural network universal machines (CNN-UM). 3. III–514. 3 indexed citations
16.
Schönmeyer, Ralf, et al.. (2003). Multi-template training for image processing with cellular neural networks. iii. 523–531. 7 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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