Reproducibility and Performance of Deep Learning Applications for Cancer Detection in Pathological Images. - Christoph Jansen; Bruno Schilling; Klaus Strohmenger; Michael Witt 001; Jonas Annuscheit; Dagmar Krefting (CCGRID, 2019)

Curious Containers: A framework for computational reproducibility in life sciences with support for Deep Learning applications. - Christoph Jansen; Jonas Annuscheit; Bruno Schilling; Klaus Strohmenger; Michael Witt 001; Felix Bartusch; Christian Herta; Peter Hufnagl; Dagmar Krefting (Future Gener. Comput. Syst., 2020)

Higher Education Teaching Material on Machine Learning in the Domain of Digital Pathology. - Klaus Strohmenger; Christian Herta; Oliver Fischer; Jonas Annuscheit; Peter Hufnagl (AI and ML for Digital Pathology, 2020)

Radial Prediction Domain Adaption Classifier for the MIDOG 2022 Challenge. - Jonas Annuscheit; Christian Krumnow (MIDOG/DRAC@MICCAI, 2022)

Radial Prediction Domain Adaption Classifier for the MIDOG 2022 challenge. - Jonas Annuscheit (CoRR, 2022)

Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge. - Marc Aubreville; Nikolas Stathonikos; Taryn A. Donovan; Robert Klopfleisch; Jonas Ammeling; Jonathan Ganz; Frauke Wilm; Mitko Veta; Samir Jabari; Markus Eckstein; Jonas Annuscheit; Christian Krumnow; et al. (Medical Image Anal., 2024)