84 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Freie Universität BerlinDE4 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE3 papers
- Technische Hochschule IngolstadtDE3 papers
- The Schwarzman Animal Medical CenterUS3 papers
- Flensburg University of Applied SciencesDE2 papers
- Michigan State UniversityUS2 papers
- Ross University School of Veterinary MedicineKN2 papers
- University of BernCH2 papers
- University of FloridaUS2 papers
- University of PennsylvaniaUS2 papers
- University of Veterinary Medicine ViennaAT2 papers
- Cornell UniversityUS1 paper
5 papers
On the Value of PHH3 for Mitotic Figure Detection on H&E-stained Images
Jonathan Ganz, Christian Marzahl, Jonas Ammeling +20
The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker as it is a measure for tumor cell proliferation. However…
Nuclear Pleomorphism in Canine Cutaneous Mast Cell Tumors: Comparison of Reproducibility and Prognostic Relevance between Estimates, Manual Morphometry and Algorithmic Morphometry
Andreas Haghofer, Eda Parlak, Alexander Bartel +18
Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurem…
LOKO: Localization-aware Roll-out Planning for Future Mobile Networks
Antonio Albanese, Vincenzo Sciancalepore, Albert Banchs +1
The roll-out phase of the next generation of mobile networks (5G) has started and operators are required to devise deployment solutions while pursuing localization accuracy maximiz…
How Many Annotators Do We Need? -- A Study on the Influence of Inter-Observer Variability on the Reliability of Automatic Mitotic Figure Assessment
Frauke Wilm, Christof A. Bertram, Christian Marzahl +23
Density of mitotic figures in histologic sections is a prognostically relevant characteristic for many tumours. Due to high inter-pathologist variability, deep learning-based algor…
Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region
Marc Aubreville, Christof A. Bertram, Christian Marzahl +9
Manual count of mitotic figures, which is determined in the tumor region with the highest mitotic activity, is a key parameter of most tumor grading schemes. It can be, however, st…