Marc Aubreville

Professor

Technische Hochschule Ingolstadt

Germany

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Articles (13)

Year:

2024

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2020

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2020

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2020

Collaborators (13)

Andreas K. Maier

GERMANY

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Maxime Lafarge

University of Basel

SWITZERLAND

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Florian Bartenschlager

Freie Universität Berlin

GERMANY

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Robert Klopfleisch

Friedrich-Loeffler-Institut

GERMANY

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Michael Dark

University of Florida

UNITED STATES

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salar razavi

Ryerson University

CANADA

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Jinah Park

Korea Advanced Institute of Science and Technology

SOUTH KOREA

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Christof Bertram

Senior lecturer

University of Veterinary Medicine Vienna

AUSTRIA

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Katharina Breininger

Professor

Julius-Maximilians-Universität Würzburg

GERMANY

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Alexander Bartel

Freie Universität Berlin

GERMANY

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Natalie ter Hoeve

UMC Utrecht

NETHERLANDS

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Konstantinos Mantsopoulos

GERMANY

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Marco Antonio Fragoso García

Research Assistant Professor

Albert Einstein College of Medicine

UNITED STATES

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Marc Aubreville

Research Interests

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Articles (13)

Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility

Prediction of tumor board procedural recommendations using large language models

Re-identification from histopathology images

Author Correction: A comprehensive multi-domain dataset for mitotic figure detection

Domain generalization across tumor types, laboratories, and species — Insights from the 2022 edition of the Mitosis Domain Generalization Challenge

Mitosis domain generalization in histopathology images — The MIDOG challenge

Segmentation metric misinterpretations in bioimage analysis

A comprehensive multi-domain dataset for mitotic figure detection

Validation of a classification and scoring system for the diagnosis of laryngeal and pharyngeal squamous cell carcinomas by confocal laser endomicroscopy

Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy

A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research

Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides

Collaborators (13)

Andreas K. Maier

Maxime Lafarge

Florian Bartenschlager

Robert Klopfleisch

Michael Dark

salar razavi

Jinah Park

Christof Bertram

Katharina Breininger

Alexander Bartel

Natalie ter Hoeve

Konstantinos Mantsopoulos

Marco Antonio Fragoso García

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