Appealing but Potentially Biasing - Investigation of the Visual Representation of Segmentation Predictions by AI Recommender Systems for Medical Decision Making.

[BibT_eX]

[DOI]

Jonas Ammeling

Carina Manger

Proceedings of the Mensch und Computer 2023, 2023

Mind the Gap: Scanner-Induced Domain Shifts Pose Challenges for Representation Learning in Histopathology.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Enabling Collagen Quantification on HE-Stained Slides through Stain Deconvolution and Restained HE-HES.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Abstract: Pan-tumor CAnine CuTaneous Cancer Histology (CATCH) Dataset.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Multi-scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Limits of Human Expert Ensembles in Mitosis Multi-expert Ground Truth Generation.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Deep Learning-based Automatic Assessment of AgNOR-scores in Histopathology Images.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Abstract: the MIDOG Challenge 2021 - Mitosis Domain Generalization in Histopathology Images.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Deep Learning-based Subtyping of Atypical and Normal Mitoses using a Hierarchical Anchor-free Object Detector.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022

Mitosis domain generalization in histopathology images - The MIDOG challenge.

[BibT_eX]

[DOI]

CoRR, 2022

Pan-Tumor CAnine cuTaneous Cancer Histology (CATCH) Dataset.

[BibT_eX]

[DOI]

CoRR, 2022

First Steps on Gamification of Lung Fluid Cells Annotations in the Flower Domain.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021

Inter-Species Cell Detection: Datasets on pulmonary hemosiderophages in equine, human and feline specimens.

[BibT_eX]

[DOI]

CoRR, 2021

Quantifying the Scanner-Induced Domain Gap in Mitosis Detection.

[BibT_eX]

[DOI]

CoRR, 2021

Learning to be EXACT, Cell Detection for Asthma on Partially Annotated Whole Slide Images.

[BibT_eX]

[DOI]

CoRR, 2021

Iterative Cross-Scanner Registration for Whole Slide Images.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Robust Quad-Tree based Registration on Whole Slide Images.

[BibT_eX]

[DOI]

Proceedings of the MICCAI Workshop on Computational Pathology, 2021

Automatic and explainable grading of meningiomas from histopathology images.

[BibT_eX]

[DOI]

Proceedings of the MICCAI Workshop on Computational Pathology, 2021

Influence of Inter-Annotator Variability on Automatic Mitotic Figure Assessment.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Cell Detection for Asthma on Partially Annotated Whole Slide Images - Learning to be EXACT.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Abstract: Are Fast Labeling Methods Reliable? - A Case Study of Computer-aided Expert Annotations on Microscopy Slides.

[BibT_eX]

[DOI]

Florian Bartenschlager

Judith Hoppe

Alina Langenhagen

Anne-Katherine Jasensky

Jörn Voigt

Robert Klopfleisch

Andreas Maier

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Abstract: Deep Learning-based Quantification of Pulmonary Hemosiderophages in Cytology Slides.

[BibT_eX]

[DOI]

Anne-Katherine Jasensky

Florian Bartenschlager

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Dataset on Bi- and Multi-nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors.

[BibT_eX]

[DOI]

Christof A. Bertram

Taryn A. Donovan

Marco Tecilla

Florian Bartenschlager

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Abstract: Deep Learning Algorithms Out-perform Veterinary Pathologists in Detecting the Mitotically Most Active Tumor Region.

[BibT_eX]

[DOI]

Florian Bartenschlager

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Abstract: A Completely Annotated Whole Slide Image Dataset of Canine Breast Cancer to Aid Human Breast Cancer Research.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020

How Many Annotators Do We Need? - A Study on the Influence of Inter-Observer Variability on the Reliability of Automatic Mitotic Figure Assessment.

[BibT_eX]

[DOI]

CoRR, 2020

Dogs as Model for Human Breast Cancer: A Completely Annotated Whole Slide Image Dataset.

[BibT_eX]

[DOI]

CoRR, 2020

EXACT: A collaboration toolset for algorithm-aided annotation of almost everything.

[BibT_eX]

[DOI]

CoRR, 2020

Are Fast Labeling Methods Reliable? A Case Study of Computer-Aided Expert Annotations on Microscopy Slides.

[BibT_eX]

[DOI]

Florian Bartenschlager

Judith Hoppe

Alina Langenhagen

Anne-Katherine Jasensky

Jörn Voigt

Robert Klopfleisch

Andreas Maier

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Are Pathologist-Defined Labels Reproducible? Comparison of the TUPAC16 Mitotic Figure Dataset with an Alternative Set of Labels.

[BibT_eX]

[DOI]

Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020

Is Crowd-Algorithm Collaboration an Advanced Alternative to Crowd-Sourcing on Cytology Slides?

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Abstract: How Big is Big Enough?

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019

Fooling the Crowd with Deep Learning-based Methods.

[BibT_eX]

[DOI]

CoRR, 2019

Learning New Tricks from Old Dogs - Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides.

[BibT_eX]

[DOI]

Anne-Katherine Jasensky

Florian Bartenschlager

CoRR, 2019

Field of Interest Prediction for Computer-Aided Mitotic Count.

[BibT_eX]

[DOI]

Florian Bartenschlager

CoRR, 2019

Field of Interest Proposal for Augmented Mitotic Cell Count: Comparison of Two Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019), 2019

Augmented Mitotic Cell Count Using Field of Interest Proposal.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018

Classification of Mitotic Cells - Potentials Beyond the Limits of Small Data Sets.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

SlideRunner - A Tool for Massive Cell Annotations in Whole Slide Images.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017

A Guided Spatial Transformer Network for Histology Cell Differentiation.

[BibT_eX]

[DOI]

Proceedings of the VCBM 17: Eurographics Workshop on Visual Computing for Biology and Medicine, 2017

Christof Bertram

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