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Institut/Einrichtung

2026

Exploring General-purpose Autonomous Multimodal Agents for Pathology Report Generation

Aubreville, M., Donovan, T. A., & Bertram, C. A. (2026). Exploring General-purpose Autonomous Multimodal Agents for Pathology Report Generation. In H. Handels, K. Breininger, T. Deserno, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Hrsg.), Bildverarbeitung für die Medizin 2026 (S. 393–399). Wiesbaden: Springer Fachmedien Wiesbaden. http://doi.org/10.1007/978-3-658-51100-5_76
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Aubreville, Marc

Forschungsprojekt

(mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

Abteilung/Einrichtung

FLAIR - Flensburg Artificial Intelligence Research

Forschungsfeld

Data Science und Künstliche Intelligenz

Fachbereich

Fachbereich 3: Information und Kommunikation
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2026

Conference Paper

Marc Aubreville

Taryn Donovan

Christof Bertram

Heinz Handels

Katharina Breininger

Thomas Deserno

Andreas Maier

Klaus Maier-Hein

Christoph Palm

Thomas Tolxdorff
Benchmarking Foundation Models for Mitotic Figure Classification

Ammeling, J., Ganz, J., Rosbach, E., Lausser, L., Bertram, C. A., Breininger, K., & Aubreville, M. (2026). Benchmarking Foundation Models for Mitotic Figure Classification. Machine Learning for Biomedical Imaging, 3, 38–58. http://doi.org/"https://doi.org/10.59275/j.melba.2026-a3eb"
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Aubreville, Marc

Forschungsprojekt

(mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

Abteilung/Einrichtung

FLAIR - Flensburg Artificial Intelligence Research

Profilbereich

Gesundheit und Life Sciences

Forschungsfeld

Data Science und Künstliche Intelligenz

Fachbereich

Fachbereich 3: Information und Kommunikation
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2026

Journal Article

Jonas Ammeling

Jonathan Ganz

Emely Rosbach

Ludwig Lausser

Christof Bertram

Katharina Breininger

Marc Aubreville
Großwärmepumpen für den kurz- bis mittelfristigen Einsatz in multivalenten Wärmeversorgungssystemen

Freißmann, J., Fritz, M., & Tuschy, I. (2026). Großwärmepumpen für den kurz- bis mittelfristigen Einsatz in multivalenten Wärmeversorgungssystemen. In J. Knies, T. Schwarz, & Y. E. Gerling (Hrsg.), Tagungsband zur 3. Konferenz der Norddeutschen Wärmeforschung (S. 54–59). Hochschule Bremen. http://doi.org/10.26092/elib/5016
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Freißmann, Jonas

Fritz, Malte

Tuschy, Ilja
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2026

Conference Paper

Jonas Freißmann

Malte Fritz

Ilja Tuschy

Jürgen Knies

Timmy Schwarz

Yannik Gerling

Wärmewende

Wärmeforschung

Energiewende

Fernwärme

Nahwärme

Transformation

Wärmeversorgung

Energieversorgung

Wärmepumpe

Wohngebäude

Wärmeplanung

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Energiespeicher
Data set creation for supervised deep learning–based analysis of microscopic images: Review of important considerations and recommendations

Bertram, C. A., Weiss, V., Ammeling, J., Schabel, M., Donovan, T. A., Wilm, F., … Aubreville, M. (2026). Data set creation for supervised deep learning–based analysis of microscopic images: Review of important considerations and recommendations. Veterinary Pathology, 03009858261457959. http://doi.org/10.1177/03009858261457959

Abstract

Supervised deep learning (DL) receives great interest for automated analysis of microscopic images with an increasing body of literature supporting its potential. The development and testing of those DL models rely heavily on the availability of high-quality, large-scale data sets. However, creating such data sets is a complex and resource-intensive process, often hindered by challenges such as time constraints, domain variability, and risks of bias in image collection and label creation. This review provides a comprehensive guide to the critical steps in data set creation, including (1) image acquisition, (2) selection of annotation software, and (3) annotation creation. For image acquisition, besides ensuring a sufficiently large number, it is important to address sources of image variability (domain shifts), such as those related to slide preparation and digitization, that could lead to algorithmic errors if not adequately represented in the training data. For annotations, key quality criteria are the 3 “C”s: correctness, consistency, and completeness. For mitigation of annotation bias of a single annotator, this review explores advanced annotation methods (eg, computer-assisted annotations). To support data set creators, a standard operating procedure is provided as supplemental material, summarizing all important considerations for data set creation. Furthermore, this article underscores the importance of open data sets in driving innovation and enhancing reproducibility of DL research. By addressing the challenges and offering practical recommendations, this review aims to advance the creation and availability of high-quality, large-scale data sets, ultimately contributing to the development of generalizable and robust DL models for pathology applications.
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Aubreville, Marc

Abteilung/Einrichtung

FLAIR - Flensburg Artificial Intelligence Research

Profilbereich

Informatik und Gestaltung

Fachbereich

Fachbereich 3: Information und Kommunikation
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2026

Journal Article

Christof Bertram

Viktoria Weiss

Jonas Ammeling

Maria Schabel

Taryn Donovan

Frauke Wilm

Christian Marzahl

Katharina Breininger

Marc Aubreville
Optimisation of the Hydraulic Variable Inertia Flywheel for Specific Energy

Rettig, A., Reese, L., & Jauch, C. (2026). Optimisation of the Hydraulic Variable Inertia Flywheel for Specific Energy. In 19. Symposium Energieinnovation 2026. Östereich, Graz. http://doi.org/https://doi.org/10.13140/RG.2.2.10150.59203

Abstract

The ongoing transition towards inverter-based generation is significantly reducing conventional rotational inertia in power systems, leading to increased rates of change of frequency. To address this challenge, the Hydraulic Variable Inertia Flywheel (HVI-FW) represents a novel alternative for distributed and inherent inertia provision. This paper presents a design tool developed to optimize the geometric parameters of the novel flywheel, with respect to specific energy. A parameter study is conducted by varying key geometric dimensions, such as radius and height. The results demonstrate that the HVI-FW can achieve significantly higher specific energy than conventional flywheels, particularly for small radii, making it well suited for coupling with small, synchronously rotating electrical machines. The findings highlight the potential of the HVI-FW as an effective solution for providing distributed inertia in future low-inertia power systems.
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Jauch, Clemens

Forschungsprojekt

Inno!Nord-HYDRAD - Hydraulischer Schwungradspeicher

Abteilung/Einrichtung

Wind Energy Technology Institute

Profilbereich

Erneuerbare Energien und nachhaltige Entwicklung

Forschungsfeld

Netzintegration

Fachbereich

Fachbereich 2: Energy and Life Science
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2026

Conference Paper

Arne Rettig

Lisanne Reese

Prof. Dr. Clemens Jauch

Flywheel, Inertia, Power System Inertia, Energy Storage, Electrical Machines
Open Source Web Dashboard zur Unterstützung der Konzeption von Wärmeversorgungssystemen

Fritz, M., Freißmann, J., & Tuschy, I. (2026). Open Source Web Dashboard zur Unterstützung der Konzeption von Wärmeversorgungssystemen. In J. Knies, T. Schwarz, & Y. E. Gerling (Hrsg.), Tagungsband zur 3. Konferenz der Norddeutschen Wärmeforschung (S. 33–38). Hochschule Bremen. http://doi.org/10.26092/elib/5016
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Fritz, Malte

Freißmann, Jonas

Tuschy, Ilja
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2026

Conference Paper

Malte Fritz

Jonas Freißmann

Ilja Tuschy

Jürgen Knies

Timmy Schwarz

Yannik Gerling

Wärmewende

Wärmeforschung

Energiewende

Fernwärme

Nahwärme

Transformation

Wärmeversorgung

Energieversorgung

Wärmepumpe

Wohngebäude

Wärmeplanung

Wärmespeicher

Wasserstoff

Energiespeicher
Reporting Transparency in Veterinary Pathology Deep Learning: A Systematic Review of Reproducibility-Critical Details

Banerjee, S., Bertram, C. A., Weiss, V., Ammeling, J., Conrad, T., Porsche, N., … Aubreville, M. (2026). Reporting Transparency in Veterinary Pathology Deep Learning: A Systematic Review of Reproducibility-Critical Details. Veterinary Pathology. http://doi.org/10.1177/03009858261459452
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Banerjee, Sweta

Porsche, Nils

Aubreville, Marc

Forschungsprojekt

(mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

Abteilung/Einrichtung

FLAIR - Flensburg Artificial Intelligence Research

Profilbereich

Informatik und Gestaltung

Forschungsfeld

Data Science und Künstliche Intelligenz

Fachbereich

Fachbereich 3: Information und Kommunikation
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2026

Journal Article

Sweta Banerjee

Christof Bertram

Viktoria Weiss

Jonas Ammeling

Thomas Conrad

Nils Porsche

Robert Klopfleisch

Christoph Stoblberger

Christopher Kaltenecker

Katharina Breininger

Marc Aubreville
A Subphase-Labeled Mitotic Dataset for AI-powered Cell Division Analysis

Ivan, Z., Hirling, D., Grexa, I., Ammeling, J., Molnar, C., Micsik, T., … Horvath, P. (2026). A Subphase-Labeled Mitotic Dataset for AI-powered Cell Division Analysis. Scientific Data. http://doi.org/10.1038/s41597-026-07007-7

Abstract

Abstract Mitosis detection represents a critical task in digital pathology, as it plays an important role in the tumor grading and prognosis of patients. Manual determination is a labor-intensive task for practitioners with high interobserver variability, thus, automation is a priority. There has been substantial progress towards creating robust mitosis detection algorithms, primarily driven by the Mitosis Domain Generalization (MIDOG) challenges. Also, there has been growing interest in the molecular characterization of mitosis to achieve a more comprehensive understanding of its underlying mechanisms in a subphase-specific manner. We introduce a new mitotic figure dataset annotated with subphase information based on the MIDOG++ dataset as well as a previously unrepresented tumor domain to enhance the diversity and applicability. We envision a new perspective for domain generalization by improving model performance with subtyping mitosis, complemented with an atypical mitotic class. Our work has implications in two main areas: subtyping information can provide helpful information in mitosis detection, while also providing promising new directions in answering biological questions, such as molecular analysis of subphases.
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Aubreville, Marc

Abteilung/Einrichtung

FLAIR - Flensburg Artificial Intelligence Research

Profilbereich

Gesundheit und Life Sciences

Forschungsfeld

Data Science und Künstliche Intelligenz

Fachbereich

Fachbereich 3: Information und Kommunikation
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2026

Journal Article

Zsanett Ivan

Dominik Hirling

Istvan Grexa

Jonas Ammeling

Csaba Molnar

Tamas Micsik

Katalin Dobra

Levente Kuthi

Farkas Sukosd

Janos Fillinger

Judit Moldvay

Erika Toth

Marc Aubreville

Vivien Miczan

Peter Horvath
Future Frequency Stabilisation by Innovative Hydraulic Variable Inertia Flywheel

Reese, L., Rettig, A., & Jauch, C. (2026). Future Frequency Stabilisation by Innovative Hydraulic Variable Inertia Flywheel. In 19. Symposium Energieinnovation 2026. http://doi.org/10.13140/RG.2.2.34154.27848
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Jauch, Clemens

Forschungsprojekt

Inno!Nord-HYDRAD - Hydraulischer Schwungradspeicher

Abteilung/Einrichtung

Wind Energy Technology Institute

Profilbereich

Erneuerbare Energien und nachhaltige Entwicklung

Forschungsfeld

Netzintegration

Fachbereich

Fachbereich 2: Energy and Life Science
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2026

Conference Paper

Lisanne Reese

Arne Rettig

Prof. Dr. Clemens Jauch

2025

Artificial intelligence predicts c-KIT exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it?

Puget, C., Ganz, J., Bertram, C. A., Conrad, T., Baeblich, M., Voss, A., … Klopfleisch, R. (2025). Artificial intelligence predicts c-KIT exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it? Veterinary Pathology, 03009858251380284. http://doi.org/10.1177/03009858251380284 (Original work published 2026)
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Aubreville, Marc

Abteilung/Einrichtung

FLAIR - Flensburg Artificial Intelligence Research

CIVU – Center for Interaction, Visualization and Usability

Profilbereich

Gesundheit und Life Sciences

Fachbereich

Fachbereich 3: Information und Kommunikation
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2025

Journal Article

Chloé Puget

Jonathan Ganz

Christof Bertram

Thomas Conrad

Malte Baeblich

Anne Voss

Katharina Landmann

Alexander Haake

Andreas Spree

Svenja Hartung

Leonore Aeschlimann

Sara Soto

Simone De Brot

Martina Dettwiler

Heike Aupperle-Lellbach

Pompei Bolfa

Alexander Bartel

Matti Kiupel

Katharina Breininger

Marc Aubreville

Robert Klopfleisch

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2026

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