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A machine learning based system for multichannel fluorescence analysis in pancreatic tissue bioimages.

J. Herold, S. Abouna, L. Zhou, S. Pelengaris, D. Epstein, M. Khan, and T. Nattkemper. BIBE, page 1-6. IEEE, (2008)

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Muhammad Khubaib ul Hassan Khan University of Stuttgart

Sogol Khanof University of Stuttgart

Univ. -Prof. Dr. Michael Pradel University of Stuttgart

LExecutor: Learning-Guided ExecutionB. Bezerra de Souza, and M. Pradel. Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, page 1522-1534. Association for Computing Machinery, (2023)

Dr. Michael Dyballa University of Stuttgart

Comparison of the Catalytic Activity of Surface-Immobilized Copper Complexes with Phosphonate Anchoring Groups for Atom Transfer Radical Cyclizations and AdditionsS. Maier, T. Nagel, M. Turan, E. Kaya, W. Frey, M. Dyballa, and D. Estes. Organometallics, 43 (3): 233-241 (2024)

Dr. Michael Böhm University of Stuttgart

Energy-optimal control of adaptive structuresM. Schaller, A. Zeller, M. Böhm, O. Sawodny, C. Tarin, and K. Worthmann. Automatisierungstechnik, 72 (2): 107-119 (2024)

Other publications of authors with the same name

Analyzing multi-tag bioimages with BioIMAX colocation mining tools.J. Kölling, M. Rathke, D. Gardner, T. Nattkemper, S. Abouna, and M. Khan. ISBI, page 1304-1307. IEEE, (2012)WHIDE - a web tool for visual data mining colocation patterns in multivariate bioimages.J. Kölling, D. Langenkämper, S. Abouna, M. Khan, and T. Nattkemper. Bioinformatics, 28 (8): 1143-1150 (2012)Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue.J. Herold, L. Zhou, S. Abouna, S. Pelengaris, D. Epstein, M. Khan, and T. Nattkemper. Comp. Med. Imag. and Graph., 34 (6): 446-452 (2010)Micro-Net: A unified model for segmentation of various objects in microscopy images.S. e Ahmed Raza, L. Cheung, M. Shaban, S. Graham, D. Epstein, S. Pelengaris, M. Khan, and N. Rajpoot. Medical Image Analysis, (2019)Micro-Net: A unified model for segmentation of various objects in microscopy images.S. e Ahmed Raza, L. Cheung, M. Shaban, S. Graham, D. Epstein, S. Pelengaris, M. Khan, and N. Rajpoot. CoRR, (2018)A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining.J. Herold, S. Abouna, L. Zhou, S. Pelengaris, D. Epstein, M. Khan, and T. Nattkemper. Medical Imaging: Image Processing, volume 7259 of SPIE Proceedings, page 72591Q. SPIE, (2009)BioIMAX: A Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data.C. Loyek, N. Rajpoot, M. Khan, and T. Nattkemper. BMC Bioinformatics, (2011)DiSWOP: a novel measure for cell-level protein network analysis in localized proteomics image data.V. Kovacheva, A. Khan, M. Khan, D. Epstein, and N. Rajpoot. Bioinformatics, 30 (3): 420-427 (2014)A Novel Paradigm for Mining Cell Phenotypes in Multi-tag Bioimages Using a Locality Preserving Nonlinear Embedding.A. Khan, A. Humayun, S. e Ahmed Raza, M. Khan, and N. Rajpoot. ICONIP (4), volume 7666 of Lecture Notes in Computer Science, page 575-583. Springer, (2012)A machine learning based system for multichannel fluorescence analysis in pancreatic tissue bioimages.J. Herold, S. Abouna, L. Zhou, S. Pelengaris, D. Epstein, M. Khan, and T. Nattkemper. BIBE, page 1-6. IEEE, (2008)