162 citations · 546 across the 19 of their papers we have counts for
6 papers · 1 filter
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Philippe Weitz, Masi Valkonen, Leslie Solorzano +38
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…
Mitosis domain generalization in histopathology images -- The MIDOG challenge
Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram +32
The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of mitoti…
Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset
Frauke Wilm, Marco Fragoso, Christian Marzahl +8
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approac…
First steps on Gamification of Lung Fluid Cells Annotations in the Flower Domain
Sonja Kunzmann, Christian Marzahl, Felix Denzinger +5
Annotating data, especially in the medical domain, requires expert knowledge and a lot of effort. This limits the amount and/or usefulness of available medical data sets for experi…
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…
Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
Christian Marzahl, Marc Aubreville, Christof A. Bertram +13
Purpose: Exercise-induced pulmonary hemorrhage (EIPH) is a common syndrome in sport horses with negative impact on performance. Cytology of bronchoalveolar lavage fluid by use of a…