Nikolas Stathonikos

Orcid: 0000-0002-5457-7580

According to our database1, Nikolas Stathonikos authored at least 16 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge.
Medical Image Anal., 2024

When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology.
CoRR, 2024

Artificial Intelligence-Based Triaging of Cutaneous Melanocytic Lesions.
CoRR, 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

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

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

2021
Quantifying the Scanner-Induced Domain Gap in Mitosis Detection.
CoRR, 2021

2020
Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images.
CoRR, 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

Segmentation and Classification of Melanoma and Nevus in Whole Slide Images.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019
Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.
Medical Image Anal., 2019

2018
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge.
CoRR, 2018


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