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20172026
most citedQuantifying the Scanner-Induced Domain Gap in Mitosis Detection

19 citations · 77 across the 23 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.HC2021

Inter-Species Cell Detection: Datasets on pulmonary hemosiderophages in equine, human and feline specimens

Christian Marzahl, Jenny Hill, Jason Stayt +9

Pulmonary hemorrhage (P-Hem) occurs among multiple species and can have various causes. Cytology of bronchoalveolarlavage fluid (BALF) using a 5-tier scoring system of alveolar mac…

eess.IV20212 cited

Automatic and explainable grading of meningiomas from histopathology images

Jonathan Ganz, Tobias Kirsch, Lucas Hoffmann +7

Meningioma is one of the most prevalent brain tumors in adults. To determine its malignancy, it is graded by a pathologist into three grades according to WHO standards. This grade…

cs.CV202119 cited

Quantifying the Scanner-Induced Domain Gap in Mitosis Detection

Marc Aubreville, Christof Bertram, Mitko Veta +6

Automated detection of mitotic figures in histopathology images has seen vast improvements, thanks to modern deep learning-based pipelines. Application of these methods, however, i…

eess.IV20211 cited

Learning to be EXACT, Cell Detection for Asthma on Partially Annotated Whole Slide Images

Christian Marzahl, Christof A. Bertram, Frauke Wilm +6

Asthma is a chronic inflammatory disorder of the lower respiratory tract and naturally occurs in humans and animals including horses. The annotation of an asthma microscopy whole s…

cs.CV2021

Dataset on Bi- and Multi-Nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors

Christof A. Bertram, Taryn A. Donovan, Marco Tecilla +8

Tumor cells with two nuclei (binucleated cells, BiNC) or more nuclei (multinucleated cells, MuNC) indicate an increased amount of cellular genetic material which is thought to faci…