output
20192024
most citedDeep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region

84 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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4 papers · 1 filter

cs.CV2024★ 8 cited

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…

cs.CV2023★ 12 cited

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…

cs.CV2021★ 12 cited

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…

cs.CV2019★ 84 cited

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…