Frauke Wilm

Orcid: 0000-0002-9065-0554

According to our database1, Frauke Wilm authored at least 31 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Analysing Diffusion Segmentation for Medical Images.
CoRR, 2024

Style-Extracting Diffusion Models for Semi-Supervised Histopathology Segmentation.
CoRR, 2024

Rethinking U-net Skip Connections for Biomedical Image Segmentation.
CoRR, 2024

Appearance-based Debiasing of Deep Learning Models in Medical Imaging.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Comprehensive Multi-domain Dataset for Mitotic Figure Detection.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023

Multi-Scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset.
Dataset, January, 2023

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

Domain generalization across tumor types, laboratories, and species - insights from the 2022 edition of the Mitosis Domain Generalization Challenge.
CoRR, 2023

Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Mind the Gap: Scanner-Induced Domain Shifts Pose Challenges for Representation Learning in Histopathology.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Improved HER2 Tumor Segmentation with Subtype Balancing Using Deep Generative Networks.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

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

Multi-scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology 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
Improved HER2 Tumor Segmentation with Subtype Balancing using Deep Generative Networks.
CoRR, 2022

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

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

Reference Algorithms for the Mitosis Domain Generalization (MIDOG) 2022 Challenge.
Proceedings of the Mitosis Domain Generalization and Diabetic Retinopathy Analysis, 2022

2021
Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmain Generalization (MIDOG) Challenge.
CoRR, 2021

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

Fast whole-slide cartography in colon cancer histology using superpixels and CNN classification.
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

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


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