Andreas Mang

545 total citations
38 papers, 297 citations indexed

About

Andreas Mang is a scholar working on Radiology, Nuclear Medicine and Imaging, Modeling and Simulation and Computer Vision and Pattern Recognition. According to data from OpenAlex, Andreas Mang has authored 38 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 17 papers in Modeling and Simulation and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Andreas Mang's work include Mathematical Biology Tumor Growth (17 papers), Medical Image Segmentation Techniques (12 papers) and MRI in cancer diagnosis (9 papers). Andreas Mang is often cited by papers focused on Mathematical Biology Tumor Growth (17 papers), Medical Image Segmentation Techniques (12 papers) and MRI in cancer diagnosis (9 papers). Andreas Mang collaborates with scholars based in Germany, United States and India. Andreas Mang's co-authors include George Biros, Thorsten M. Buzug, Amir Gholami, Stefan Becker, Christos Davatzikos, Edouard Timsit, Calvin W. Booker, Sébastien Buczinski, Miriam Mehl and Spyridon Bakas and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Journal of Dairy Science.

In The Last Decade

Andreas Mang

35 papers receiving 286 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 Mang Germany 11 96 90 80 38 36 38 297
Guang Zhang China 17 156 1.6× 19 0.2× 18 0.2× 3 0.1× 27 0.8× 101 1.0k
Sewoong Kim South Korea 9 22 0.2× 49 0.5× 42 0.5× 3 0.1× 63 1.8× 28 329
Ophir Nave Israel 10 88 0.9× 12 0.1× 6 0.1× 5 0.1× 31 0.9× 45 275
Mihaela Oprea United States 11 27 0.3× 82 0.9× 5 0.1× 16 0.4× 159 4.4× 15 484
Tuan Anh Phan United States 10 47 0.5× 3 0.0× 19 0.2× 8 0.2× 107 3.0× 34 309
Daniel Jiménez‐Carretero Spain 13 9 0.1× 155 1.7× 94 1.2× 5 0.1× 105 2.9× 36 575
Laura Antonelli Italy 13 2 0.0× 27 0.3× 33 0.4× 12 0.3× 237 6.6× 34 485
Nisrine Outada Morocco 8 229 2.4× 7 0.1× 11 0.1× 1 0.0× 70 1.9× 14 413
Geoffrey W. Hoffmann Canada 12 15 0.2× 97 1.1× 8 0.1× 12 0.3× 262 7.3× 38 701
Sayan Mukherjee India 13 91 0.9× 7 0.1× 44 0.6× 1 0.0× 115 3.2× 43 422

Countries citing papers authored by Andreas Mang

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Mang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Mang

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Mang. A scholar is included among the top collaborators of Andreas Mang 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 Mang. Andreas Mang 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.
Mang, Andreas, Jiwen He, & Robert Azencott. (2023). An operator-splitting approach for variational optimal control formulations for diffeomorphic shape matching. Journal of Computational Physics. 493. 112463–112463.
2.
Biros, George, et al.. (2021). CLAIRE: Constrained Large Deformation Diffeomorphic Image Registration on Parallel Computing Architectures. The Journal of Open Source Software. 6(61). 3038–3038. 2 indexed citations
3.
Muley, Thomas, Matthias Schneider, Michael Meister, et al.. (2021). P23.04 Serum Biomarkers Enhance Prognostic Value of Computed Tomography (CT) in Patients With Non-Small Cell Lung Cancer (NSCLC). Journal of Thoracic Oncology. 16(10). S1028–S1029. 3 indexed citations
4.
Biros, George, et al.. (2020). Fast GPU 3D diffeomorphic image registration. Journal of Parallel and Distributed Computing. 149. 149–162. 13 indexed citations
5.
Scheufele, Klaudius, Andreas Mang, Amir Gholami, et al.. (2019). Coupling brain-tumor biophysical models and diffeomorphic image registration. Computer Methods in Applied Mechanics and Engineering. 347. 533–567. 19 indexed citations
6.
Jaureguiberry, María, Maurício Javier Giuliodori, Andreas Mang, et al.. (2017). Short communication: Repeat breeder cows with fluid in the uterine lumen had poorer fertility. Journal of Dairy Science. 100(4). 3083–3085. 8 indexed citations
7.
Gholami, Amir, Andreas Mang, Klaudius Scheufele, et al.. (2017). A framework for scalable biophysics-based image analysis. Fachbereich Informatik (University of Stuttgart). 1–13. 5 indexed citations
8.
Gholami, Amir, Andreas Mang, & George Biros. (2015). An inverse problem formulation for parameter estimation of a reaction–diffusion model of low grade gliomas. Journal of Mathematical Biology. 72(1-2). 409–433. 48 indexed citations
9.
Mang, Andreas, Sébastien Buczinski, Calvin W. Booker, & Edouard Timsit. (2015). Evaluation of a Computer-aided Lung Auscultation System for Diagnosis of Bovine Respiratory Disease in Feedlot Cattle. Journal of Veterinary Internal Medicine. 29(4). 1112–1116. 30 indexed citations
10.
Gholami, Amir, Andreas Mang, & George Biros. (2014). Image-driven parameter estimation for low grade gliomas. arXiv (Cornell University). 1 indexed citations
11.
Becker, Stefan, et al.. (2013). Modelling of glioblastoma growth by linking a molecular interaction network with an agent-based model. Mathematical and Computer Modelling of Dynamical Systems. 19(5). 417–433. 8 indexed citations
12.
Becker, Stefan, et al.. (2013). A Validated Mathematical Model of Tumour-Immune Interactions for Glioblastoma. Current Medical Imaging Formerly Current Medical Imaging Reviews. 9(2). 145–153. 5 indexed citations
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15.
Mang, Andreas, Stefan Becker, Thomas Eckey, et al.. (2012). Biophysical modeling of brain tumor progression: From unconditionally stable explicit time integration to an inverse problem with parabolic PDE constraints for model calibration. Medical Physics. 39(7Part1). 4444–4459. 19 indexed citations
16.
Holl‐Ulrich, Konstanze, Stefan Becker, Andreas Mang, et al.. (2012). A Mathematical Model to Simulate Glioma Growth and Radiotherapy at the Microscopic Level. Biomedizinische Technik/Biomedical Engineering. 57(SI-1 Track-O). 1 indexed citations
17.
Mang, Andreas, et al.. (2011). Is it Necessary to Model the Matrix Degrading Enzymes for Simulating Tumour Growth?. Eurographics. 1 indexed citations
18.
Becker, Stefan, et al.. (2010). In-silico oncology: an approximate model of brain tumor mass effect based on directly manipulated free form deformation. International Journal of Computer Assisted Radiology and Surgery. 5(6). 607–622. 10 indexed citations
19.
Mang, Andreas, et al.. (2010). Coupling tumor growth with brain deformation: a constrained parametric non-rigid registration problem. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7623. 76230C–76230C. 4 indexed citations
20.
Müller, Jan, Andreas Mang, & Thorsten M. Buzug. (2005). A template-deformation method for facial reproduction. 359–364. 9 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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