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M. Kiupel

3 papers hereh-index 499.7k citations358 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV1
same name
  • M. Kiupel — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212023
most citedNuclear Pleomorphism in Canine Cutaneous Mast Cell Tumors: Comparison of Reproducibility and Prognostic Relevance between Estimates, Manual Morphometry and Algorithmic Morphometry

12 citations · 24 across the 3 of their papers we have counts for

collaborators

3 papers

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…

eess.IV2022

Deep Learning-Based Automatic Assessment of AgNOR-scores in Histopathology Images

Jonathan Ganz, Karoline Lipnik, Jonas Ammeling +10

Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription. Due to the silver affinity of associated proteins, argyrophilic NORs (AgNORs) can be…

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…

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