Christian Marzahl

Orcid: 0000-0001-9340-9873

According to our database1, Christian Marzahl authored at least 36 papers between 2012 and 2024.

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Bibliography

2024
Abstract: Cytologic Scoring of Equine Exercise-induced Pulmonary Hemorrhage - Performance of Human Experts and a Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Mitosis domain generalization in histopathology images - The MIDOG challenge.
Medical Image Anal., 2023

The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue.
CoRR, 2023

Abstract: Pan-tumor CAnine CuTaneous Cancer Histology (CATCH) Dataset.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Abstract: the MIDOG Challenge 2021 - Mitosis Domain Generalization in Histopathology Images.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Deep Learning-based Cell Detection in Microscopy Images.
PhD thesis, 2022

Mitosis domain generalization in histopathology images - The MIDOG challenge.
CoRR, 2022

Pan-Tumor CAnine cuTaneous Cancer Histology (CATCH) Dataset.
CoRR, 2022

Superpixel Pre-segmentation of HER2 Slides for Efficient Annotation.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

First Steps on Gamification of Lung Fluid Cells Annotations in the Flower Domain.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021
Inter-Species Cell Detection: Datasets on pulmonary hemosiderophages in equine, human and feline specimens.
CoRR, 2021

Learning to be EXACT, Cell Detection for Asthma on Partially Annotated Whole Slide Images.
CoRR, 2021

Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmain Generalization Challenge.
Proceedings of the Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis - MICCAI 2021 Challenges: MIDOG 2021, MOOD 2021, and Learn2Reg 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021

Iterative Cross-Scanner Registration for Whole Slide Images.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Robust Quad-Tree based Registration on Whole Slide Images.
Proceedings of the MICCAI Workshop on Computational Pathology, 2021


Cell Detection for Asthma on Partially Annotated Whole Slide Images - Learning to be EXACT.
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.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Abstract: Deep Learning-based Quantification of Pulmonary Hemosiderophages in Cytology Slides.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Dataset on Bi- and Multi-nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors.
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.
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.
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.
CoRR, 2020

Dogs as Model for Human Breast Cancer: A Completely Annotated Whole Slide Image Dataset.
CoRR, 2020

EXACT: A collaboration toolset for algorithm-aided annotation of almost everything.
CoRR, 2020

Are Fast Labeling Methods Reliable? A Case Study of Computer-Aided Expert Annotations on Microscopy Slides.
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.
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?
Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Abstract: How Big is Big Enough?
Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment.
Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019
Fooling the Crowd with Deep Learning-based Methods.
CoRR, 2019

Learning New Tricks from Old Dogs - Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment.
CoRR, 2019

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides.
CoRR, 2019

Field of Interest Prediction for Computer-Aided Mitotic Count.
CoRR, 2019

Synthetic Training with Generative Adversarial Networks for Segmentation of Microscopies.
Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2012
Unobtrusive Fall Detection and Prevention: Extending From a Prototype Test to a Pilot Trial.
Proceedings of the 57. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie, 42. Jahrestagung der Gesellschaft für Informatik, Was bewegt uns in der/die Zukunft?, 2012


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