K. Rohr

804 total citations
39 papers, 479 citations indexed

About

K. Rohr is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, K. Rohr has authored 39 papers receiving a total of 479 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Biophysics, 16 papers in Computer Vision and Pattern Recognition and 11 papers in Media Technology. Recurrent topics in K. Rohr's work include Cell Image Analysis Techniques (20 papers), Image Processing Techniques and Applications (11 papers) and AI in cancer detection (6 papers). K. Rohr is often cited by papers focused on Cell Image Analysis Techniques (20 papers), Image Processing Techniques and Applications (11 papers) and AI in cancer detection (6 papers). K. Rohr collaborates with scholars based in Germany, Netherlands and Canada. K. Rohr's co-authors include Roland Eils, Stefan Wörz, Thomas Wollmann, William J. Godinez, Bárbara Müller, Marko Lampe, Pascal Cathier, Holger Erfle, Karsten Rippe and I‐Fang Chung and has published in prestigious journals such as Developmental Biology, Journal of Biomechanics and IEEE Transactions on Medical Imaging.

In The Last Decade

K. Rohr

38 papers receiving 464 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Rohr Germany 13 216 156 134 79 77 39 479
Nathalie Harder Germany 15 154 0.7× 73 0.5× 206 1.5× 70 0.9× 60 0.8× 31 525
Isabel Vallcorba Spain 8 227 1.1× 172 1.1× 143 1.1× 130 1.6× 96 1.2× 17 566
Piyush Goyal India 5 254 1.2× 62 0.4× 159 1.2× 96 1.2× 99 1.3× 13 682
Ryoma Bise Japan 14 289 1.3× 240 1.5× 111 0.8× 145 1.8× 182 2.4× 54 636
Ilker Ersoy United States 16 183 0.8× 502 3.2× 121 0.9× 200 2.5× 114 1.5× 43 897
Alberto Santamaría-Pang United States 13 120 0.6× 52 0.3× 228 1.7× 34 0.4× 46 0.6× 32 544
Grégory Paul Switzerland 6 135 0.6× 82 0.5× 179 1.3× 38 0.5× 42 0.5× 11 482
Dylan Bannon United States 3 438 2.0× 107 0.7× 268 2.0× 118 1.5× 159 2.1× 3 871
Stefan Wörz Germany 17 160 0.7× 296 1.9× 295 2.2× 37 0.5× 50 0.6× 68 978
Petr Matula Czechia 14 149 0.7× 77 0.5× 219 1.6× 26 0.3× 65 0.8× 43 476

Countries citing papers authored by K. Rohr

Since Specialization
Citations

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

Fields of papers citing papers by K. Rohr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Rohr

This figure shows the co-authorship network connecting the top 25 collaborators of K. Rohr. A scholar is included among the top collaborators of K. Rohr 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 K. Rohr. K. Rohr 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.
Ritter, Christian, Thomas Wollmann, Andrea Imle, et al.. (2021). Data fusion and smoothing for probabilistic tracking of viral structures in fluorescence microscopy images. Medical Image Analysis. 73. 102168–102168. 10 indexed citations
2.
Ritter, Christian, et al.. (2021). Deep Learning For Particle Detection And Tracking In Fluorescence Microscopy Images. 873–876. 3 indexed citations
3.
Ritter, Christian, et al.. (2020). Deep Learning Particle Detection for Probabilistic Tracking in Fluorescence Microscopy Images. 977–980. 6 indexed citations
4.
Kostrykin, Leonid, Christoph Schnörr, & K. Rohr. (2019). Globally optimal segmentation of cell nuclei in fluorescence microscopy images using shape and intensity information. Medical Image Analysis. 58. 101536–101536. 12 indexed citations
5.
Wollmann, Thomas, Manuel Gunkel, I‐Fang Chung, et al.. (2019). GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation. Medical Image Analysis. 56. 68–79. 55 indexed citations
6.
Miró, Joaquim, et al.. (2018). Personalized stent design for congenital heart defects using pulsatile blood flow simulations. Journal of Biomechanics. 81. 68–75. 11 indexed citations
7.
Erfle, Holger, Nathalie Harder, K. Rohr, et al.. (2015). Targeting mitosis‐regulating genes in cisplatin‐sensitive and ‐resistant melanoma cells: A live‐cell RNAi screen displays differential nucleus‐derived phenotypes. Biotechnology Journal. 10(9). 1467–1477. 3 indexed citations
8.
Raiss, Patric, Boris Sowa, Thomas Brückner, et al.. (2012). Pressurisation leads to better cement penetration into the glenoid bone. Journal of Bone and Joint Surgery - British Volume. 94-B(5). 671–677. 15 indexed citations
9.
Godinez, William J., Marko Lampe, Roland Eils, Bárbara Müller, & K. Rohr. (2011). Tracking multiple particles in fluorescence microscopy images via probabilistic data association. 10 indexed citations
10.
Wörz, Stefan, Martin Pfannmöller, R. J. Rieker, et al.. (2010). 3D Geometry-Based Quantification of Colocalizations in Multichannel 3D Microscopy Images of Human Soft Tissue Tumors. IEEE Transactions on Medical Imaging. 29(8). 1474–1484. 20 indexed citations
11.
Godinez, William J., Marko Lampe, Stefan Wörz, et al.. (2009). Deterministic and probabilistic approaches for tracking virus particles in time-lapse fluorescence microscopy image sequences. Medical Image Analysis. 13(2). 325–342. 88 indexed citations
12.
Godinez, William J., Marko Lampe, Stefan Wörz, et al.. (2009). Identifying fusion events in fluorescence microscopy images. 1170–1173. 4 indexed citations
13.
Harder, Nathalie, Roland Eils, & K. Rohr. (2008). Automated Classification of Mitotic Phenotypes of Human Cells Using Fluorescent Proteins. Methods in cell biology. 85. 539–554. 16 indexed citations
14.
Godinez, William J., Marko Lampe, Stefan Wörz, et al.. (2008). Probabilistic tracking of virus particles in fluorescence microscopy images. 272–275. 3 indexed citations
15.
Gladilin, Evgeny, Sandra Goetze, Julio Mateos‐Langerak, et al.. (2008). Shape normalization of 3D cell nuclei using elastic spherical mapping. Journal of Microscopy. 231(1). 105–114. 16 indexed citations
16.
Gladilin, Evgeny, et al.. (2007). 3D finite element analysis of uniaxial cell stretching: from image to insight. Physical Biology. 4(2). 104–113. 33 indexed citations
17.
Yang, Sen, Patricia Le Baccon, Édith Heard, et al.. (2007). NON-RIGID TEMPORAL REGISTRATION OF 2D AND 3D MULTI-CHANNEL MICROSCOPY IMAGE SEQUENCES OF HUMAN CELLS. 1328–1331. 8 indexed citations
18.
Harder, Nathalie, Beate Neumann, Michael Held, et al.. (2006). Automated Recognition of Mitotic Patterns in Fluorescence Microscopy Images of Human Cells. 1016–1019. 15 indexed citations
19.
Rohr, K., Pascal Cathier, & Stefan Wörz. (2004). Elastic registration of electrophoresis images using intensity information and point landmarks. Pattern Recognition. 37(5). 1035–1048. 39 indexed citations
20.
Tautz, Diethard, et al.. (1999). Evolution of insect segmentation.. Developmental Biology. 210(1). 243–243. 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.

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