Andreas Degenhard

899 total citations
30 papers, 559 citations indexed

About

Andreas Degenhard is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Condensed Matter Physics. According to data from OpenAlex, Andreas Degenhard has authored 30 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 12 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Condensed Matter Physics. Recurrent topics in Andreas Degenhard's work include AI in cancer detection (7 papers), Theoretical and Computational Physics (7 papers) and MRI in cancer diagnosis (6 papers). Andreas Degenhard is often cited by papers focused on AI in cancer detection (7 papers), Theoretical and Computational Physics (7 papers) and MRI in cancer diagnosis (6 papers). Andreas Degenhard collaborates with scholars based in Germany, United Kingdom and Spain. Andreas Degenhard's co-authors include Martin O. Leach, Tim W. Nattkemper, Christine Tanner, Julia A. Schnabel, D. Rodney Hose, David Hill, Friederike Schmid, David J. Hawkes, Carmel Hayes and Alexey A. Polotsky and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and Physical review. B, Condensed matter.

In The Last Decade

Andreas Degenhard

28 papers receiving 537 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andreas Degenhard Germany 13 282 193 137 101 52 30 559
Yang‐Ming Zhu China 11 211 0.7× 171 0.9× 37 0.3× 110 1.1× 64 1.2× 47 666
Munendra Singh India 16 145 0.5× 199 1.0× 113 0.8× 59 0.6× 30 0.6× 79 781
G. Raso Italy 19 315 1.1× 191 1.0× 269 2.0× 275 2.7× 75 1.4× 71 955
Shaoguo Cui China 9 106 0.4× 134 0.7× 79 0.6× 54 0.5× 8 0.2× 55 417
Shuxu Guo China 20 282 1.0× 298 1.5× 166 1.2× 213 2.1× 8 0.2× 83 1.1k
Jacqueline Ngo United States 15 89 0.3× 144 0.7× 55 0.4× 130 1.3× 110 2.1× 33 610
Jacob Hinkle United States 15 163 0.6× 101 0.5× 115 0.8× 94 0.9× 51 1.0× 47 578
Lionel Hervé France 15 341 1.2× 49 0.3× 63 0.5× 393 3.9× 40 0.8× 63 680
Viktor Vegh Australia 15 373 1.3× 58 0.3× 20 0.1× 104 1.0× 75 1.4× 93 783
Savvas Damaskinos Canada 12 85 0.3× 81 0.4× 117 0.9× 120 1.2× 20 0.4× 42 436

Countries citing papers authored by Andreas Degenhard

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Degenhard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Degenhard

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Degenhard. A scholar is included among the top collaborators of Andreas Degenhard 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 Andreas Degenhard. Andreas Degenhard 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.
Nattkemper, Tim W., et al.. (2007). A method for linking computed image features to histological semantics in neuropathology. Journal of Biomedical Informatics. 40(6). 631–641. 36 indexed citations
2.
Behrinǵer, Hans, et al.. (2007). Developing and analyzing idealized models for molecular recognition. Journal of Biotechnology. 129(2). 268–278. 4 indexed citations
3.
Tanner, Christine, Julia A. Schnabel, David Hill, et al.. (2007). Quantitative evaluation of free‐form deformation registration for dynamic contrast‐enhanced MR mammography. Medical Physics. 34(4). 1221–1233. 33 indexed citations
4.
Nattkemper, Tim W., et al.. (2007). Multiscale analysis of MR-mammography data. Zeitschrift für Medizinische Physik. 17(3). 166–171.
5.
Behrinǵer, Hans, Andreas Degenhard, & Friederike Schmid. (2007). Coarse-grained lattice model for investigating the role of cooperativity in molecular recognition. Physical Review E. 76(3). 31914–31914. 3 indexed citations
6.
Behrinǵer, Hans, Andreas Degenhard, & Friederike Schmid. (2006). Coarse-Grained Lattice Model for Molecular Recognition. Physical Review Letters. 97(12). 128101–128101. 15 indexed citations
7.
Degenhard, Andreas, et al.. (2006). Visual exploratory analysis of DCE-MRI data in breast cancer by dimensional data reduction: A comparative study. Biomedical Signal Processing and Control. 1(1). 56–63. 12 indexed citations
8.
Degenhard, Andreas, et al.. (2006). Histologic characterization of DCE-MRI breast tumors with dimensional data reduction. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6144. 614462–614462. 1 indexed citations
9.
Degenhard, Andreas & Javier Rodríguez-Laguna. (2005). Construction of Projection Operators for Nonlinear Evolutionary Dynamics. Multiscale Modeling and Simulation. 4(2). 641–663. 2 indexed citations
10.
Nattkemper, Tim W., et al.. (2005). Breast MRI data analysis by LLE. 3. 2449–2454. 35 indexed citations
11.
Twellmann, Thorsten, et al.. (2004). Wavelet features for improved tumour detection in DCE-MRI. PUB – Publications at Bielefeld University (Bielefeld University).
12.
Degenhard, Andreas, et al.. (2004). Molecular Recognition in a Lattice Model: An Enumeration Study. Physical Review Letters. 93(26). 268108–268108. 24 indexed citations
13.
Polotsky, Alexey A., Friederike Schmid, & Andreas Degenhard. (2004). Polymer adsorption onto random planar surfaces: Interplay of polymer and surface correlations. The Journal of Chemical Physics. 121(10). 4853–4864. 24 indexed citations
14.
Nattkemper, Tim W., et al.. (2004). Visualisation of Breast Tumour DCE-MRI Data using LLE. PUB – Publications at Bielefeld University (Bielefeld University). 100. 2 indexed citations
15.
Nattkemper, Tim W., Bert Arnrich, Andreas Degenhard, et al.. (2004). Evaluation of radiological features for breast tumour classification in clinical screening with machine learning methods. Artificial Intelligence in Medicine. 34(2). 129–139. 53 indexed citations
16.
Polotsky, Alexey A., Friederike Schmid, & Andreas Degenhard. (2004). Influence of sequence correlations on the adsorption of random heteropolymers onto homogeneous planar surfaces. The Journal of Chemical Physics. 120(13). 6246–6256. 16 indexed citations
17.
Schnabel, Julia A., Christine Tanner, Andreas Degenhard, et al.. (2003). Validation of nonrigid image registration using finite-element methods: application to breast MR images. IEEE Transactions on Medical Imaging. 22(2). 238–247. 175 indexed citations
18.
Degenhard, Andreas, et al.. (2002). Comparison between radiological and artificial neural network diagnosis in clinical screening. Physiological Measurement. 23(4). 727–739. 18 indexed citations
19.
Degenhard, Andreas & Javier Rodríguez-Laguna. (2002). Real-space renormalization-group approach to field evolution equations. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 65(3). 36703–36703. 3 indexed citations
20.
Degenhard, Andreas, Christine Tanner, Carmel Hayes, D.J. Hawkes, & Martin O. Leach. (2001). Pre-processed image reconstruction applied to breast and brain MR imaging. Physiological Measurement. 22(3). 589–604. 2 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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