Grouping for Random Marked Point Processes. - Peter Hufnagl; Klaus Voss (J. Inf. Process. Cybern., 1984)

The virtual microscope for routine pathology based on a PACS system for 6 Gb images. - Kai Saeger; Karsten Schlüns; Thomas Schrader; Peter Hufnagl (CARS, 2003)

Image Quality Assessment in Digital Pathology - The Analysis of Background in Whole Slide Images. - Thomas Schrader; Anne Nadolny; Robert Piduch; Peter Hufnagl (IWBBIO, 2014)

Appearance-based necrosis detection using textural features and SVM with discriminative thresholding in histopathological whole slide images. - Harshita Sharma; Norman Zerbe; Iris Klempert; Sebastian Lohmann; Björn Lindequist; Olaf Hellwich; Peter Hufnagl (BIBE, 2015)

Next generation biobanks. - Christian Seebode; Matthias Ort; Peter Hufnagl; Christian R. A. Regenbrecht (IEEE BigData, 2015)

Gestenbasierte Interaktionsmethoden für die virtuelle Mikroskopie. - Arend Müller; Thorsten Knape; Peter Hufnagl (Bildverarbeitung für die Medizin, 2015)

A Multi-resolution Approach for Combining Visual Information using Nuclei Segmentation and Classification in Histopathological Images. - Harshita Sharma; Norman Zerbe; Daniel Heim; Stephan Wienert; Hans-Michael Behrens; Olaf Hellwich; Peter Hufnagl (VISAPP (3), 2015)

Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology. - Harshita Sharma; Norman Zerbe; Daniel Heim; Stephan Wienert; Sebastian Lohmann; Olaf Hellwich; Peter Hufnagl (Digital Pathology, 2016)

A Comparative Study of Cell Nuclei Attributed Relational Graphs for Knowledge Description and Categorization in Histopathological Gastric Cancer Whole Slide Images. - Harshita Sharma; Norman Zerbe; Christine Boger; Stephan Wienert; Olaf Hellwich; Peter Hufnagl (CBMS, 2017)

Preface. - Daniel Racoceanu; Peter Hufnagl (Comput. Medical Imaging Graph., 2017)

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology. - Harshita Sharma; Norman Zerbe; Iris Klempert; Olaf Hellwich; Peter Hufnagl (Comput. Medical Imaging Graph., 2017)

Computational morphogenesis - Embryogenesis, cancer research and digital pathology. - Pridi Siregar; Nathalie Julen; Peter Hufnagl; George L. Mutter (Biosyst., 2018)

A general framework dedicated to computational morphogenesis Part I - Constitutive equations. - Pridi Siregar; Nathalie Julen; Peter Hufnagl; George L. Mutter (Biosyst., 2018)

A general framework dedicated to computational morphogenesis Part II - Knowledge representation and architecture. - Pridi Siregar; Nathalie Julen; Peter Hufnagl; George L. Mutter (Biosyst., 2018)

A Gray-box Testing Method for Divide&Conquer in Image Processing. - Marco Strutz; Hermann Heßling; Peter Hufnagl (IEEE BigData, 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)

OBDEX - Open Block Data Exchange System. - Björn Lindequist; Norman Zerbe; Peter Hufnagl (AI and ML for Digital Pathology, 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)

Assessment and Comparison of Colour Fidelity of Whole Slide Imaging Scanners. - Norman Zerbe; Alexander Alekseychuk; Peter Hufnagl (AI and ML for Digital Pathology, 2020)

Extension of the Identity Management System Mainzelliste to Reduce Runtimes for Patient Registration in Large Datasets. - Norman Zerbe; Christopher Hampf; Peter Hufnagl (AI and ML for Digital Pathology, 2020)

On Divide&Conquer in Image Processing of Data Monster. - Hermann Heßling; Marco Strutz; Elsa Irmgard Buchholz; Peter Hufnagl (Big Data Res., 2021)

EMPAIA App Interface: An open and vendor-neutral interface for AI applications in pathology. - Daniel Romberg; Klaus Strohmenger; Christoph Jansen; Tobias Küster; Nick Weiss; Christian Geißler; Tomasz Soltysinski; Michael Takla; Peter Hufnagl; Norman Zerbe; André Homeyer (Comput. Methods Programs Biomed., 2022)

Recommendations on test datasets for evaluating AI solutions in pathology. - André Homeyer; Christian Geißler; Lars Ole Schwen; Falk Zakrzewski; Theodore Evans; Klaus Strohmenger; Max Westphal; Roman David Bülow; Michaela Kargl; Aray Karjauv; Isidre Munné-Bertran; Carl Orge Retzlaff; et al. (CoRR, 2022)

Anonymization of Whole Slide Images in Histopathology for Research and Education. - Tom Bisson; Michael Franz; Isil Dogan O; Daniel Romberg; Christoph Jansen; Peter Hufnagl; Norman Zerbe (CoRR, 2022)

Joining Forces for Pathology Diagnostics with AI Assistance: The EMPAIA Initiative. - Norman Zerbe; Lars Ole Schwen; Christian Geißler; Katja Wiesemann; Tom Bisson; Peter Boor; Rita Carvalho; Michael Franz; Christoph Jansen; Tim-Rasmus Kiehl; Björn Lindequist; Nora Charlotte Pohlan; et al. (CoRR, 2024)

Volumetric Reconstruction of Prostatectomy Specimens from Histology. - Tom Bisson; Isil Dogan O; Iris Piwonski; Tim-Rasmus Kiehl; Georg Lukas Baumgärtner; Rita Carvalho; Peter Hufnagl; Tobias Penzkofer; Norman Zerbe; Sefer Elezkurtaj (CoRR, 2024)

A high-precision hierarchical registration approach for stain- and scanner-independent colocalization on whole slide images in histopathology. - Tom Bisson; Michael Franz; Tim-Rasmus Kiehl; Peter Boor; Peter Hufnagl; Norman Zerbe (Health Inf. Sci. Syst., 2025)