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2020 – today
- 2020
[j2]Dan Guo, Melanie Christine Föll
, Veronika Volkmann, Kathrin Enderle-Ammour, Peter Bronsert, Oliver Schilling, Olga Vitek:
Deep multiple instance learning classifies subtissue locations in mass spectrometry images from tissue-level annotations. Bioinform. 36(Supplement-1): i300-i308 (2020)- [i1]Dejan Kostyszyn, Tobias Fechter, Nico Bartl, Anca L. Grosu, Christian Gratzke, August Sigle, Michael Mix, Juri Ruf, Thomas F. Fassbender, Selina Kiefer, Alisa S. Bettermann, Nils H. Nicolay, Simon Spohn, Maria U. Kramer, Peter Bronsert, Hongqian Guo, Xuefeng Qiu, Feng Wang, Christoph Henkenberens, Rudolf A. Werner, Dimos Baltas, Philipp T. Meyer, Thorsten Derlin, Mengxia Chen, Constantinos Zamboglou:
Convolutional neural network based deep-learning architecture for intraprostatic tumour contouring on PSMA PET images in patients with primary prostate cancer. CoRR abs/2008.03201 (2020)
2010 – 2019
- 2016
- [j1]Martin Boeker, Fábio França, Peter Bronsert, Stefan Schulz:
TNM-O: ontology support for staging of malignant tumours. J. Biomed. Semant. 7: 64:1-64:11 (2016) - 2015
- [c2]Martin Boeker, Fábio França, Peter Bronsert, Stefan Schulz:
TNM-O an ontology for the Tumor-Node-Metastasis classification of malignant tumors: a study on rectal cancer. ICBO 2015 - [c1]Fábio França, Stefan Schulz, Peter Bronsert, Paulo Novais, Martin Boeker:
Feasibility of an ontology driven tumor-node-metastasis classifier application: A study on colorectal cancer. INISTA 2015: 1-7
Coauthor Index
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