Christian Marzahl, M. Sc.
- Since 04/2019:
Department of Computer Science
2017
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Digital Pathology - New Approaches to the Automated Image Analysis of Histologic Slides
(Own Funds)
Term: since January 16, 2017The pathologist is still the gold standard in the diagnosis of diseases in tissue slides. Due to its human nature, the pathologist is on one side able to flexibly adapt to the high morphological and technical variability of histologic slides but of limited objectivity due to cognitive and visual traps.
In diverse project we are applying and validating currently available tools and solutions in digital pathology but are also developing new solution in automated image analysis to complement and improve the pathologist especially in areas of quantitative image analysis.
2020
Journal Articles
A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research
In: Scientific Data 7 (2020), Article No.: 417
ISSN: 2052-4463
DOI: 10.1038/s41597-020-00756-z
BibTeX: Download
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Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region
In: Scientific Reports 10 (2020), Article No.: 16447
ISSN: 2045-2322
DOI: 10.1038/s41598-020-73246-2
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Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides
In: Scientific Reports 10 (2020), Article No.: 9795
ISSN: 2045-2322
DOI: 10.1038/s41598-020-65958-2
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Book Contributions
Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment - Learning New Tricks from Old Dogs
In: Tolxdorff T., Deserno T., Handels H., Maier A., Maier-Hein K., Palm C. (ed.): Bildverarbeitung für die Medizin 2020, Wiesbaden: Springer Vieweg, 2020, p. 1-7
ISBN: 9783658292669
DOI: 10.1007/978-3-658-29267-6_1
URL: https://arxiv.org/pdf/1911.10873.pdf
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Conference Contributions
How Big is Big Enough?: A Large-Scale Histological Dataset of Mitotic Figures
Bildverarbeitung für die Medizin 2020 (Berlin, March 17, 2020 - March 19, 2020)
In: Tolxdorff T., Deserno T., Handels H., Maier A., Maier-Hein K., Palm C. (ed.): Bildverarbeitung für die Medizin 2020, Wiesbaden: 2020
DOI: 10.1007/978-3-658-29267-6_65
URL: https://link.springer.com/content/pdf/10.1007/978-3-658-29267-6_65.pdf
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Are fast labeling methods reliable? a case study of computer-aided expert annotations on microscopy slides
23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 (Lima, October 4, 2020 - October 8, 2020)
In: Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2020
DOI: 10.1007/978-3-030-59710-8_3
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Is crowd-algorithm collaboration an advanced alternative to crowd-sourcing on cytology slides?
International workshop on Algorithmen - Systeme - Anwendungen, 2020 (Berlin, March 15, 2020 - March 17, 2020)
In: Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (ed.): Informatik aktuell 2020
DOI: 10.1007/978-3-658-29267-6_5
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Are Pathologist-Defined Labels Reproducible? Comparison of the TUPAC16 Mitotic Figure Dataset with an Alternative Set of Labels
IMIMIC 2020, MIL3ID 2020, LABELS 2020 (Lima, October 4, 2020 - October 8, 2020)
In: Jaime Cardoso, Wilson Silva, Ricardo Cruz, Hien Van Nguyen, Badri Roysam, Nicholas Heller, Pedro Henriques Abreu, Jose Pereira Amorim, Ivana Isgum, Vishal Patel, Kevin Zhou, Steve Jiang, Ngan Le, Khoa Luu, Raphael Sznitman, Veronika Cheplygina, Samaneh Abbasi, Diana Mateus, Emanuele Trucco (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2020
DOI: 10.1007/978-3-030-61166-8_22
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2019
Journal Articles
A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor
In: Scientific Data 6 (2019), p. 1-9
ISSN: 2052-4463
DOI: 10.1038/s41597-019-0290-4
URL: https://www.nature.com/articles/s41597-019-0290-4.pdf
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Book Contributions
Classification of leukemic B-Lymphoblast cells from blood smear microscopic images with an attention-based deep learning method and advanced augmentation techniques
In: Anubha Gupta, Ritu Gupta (ed.): ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging, Springer, 2019, p. 13-22 (Lecture Notes in Bioengineering)
DOI: 10.1007/978-981-15-0798-4_2
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Seminar (SEM)
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Seminar Digital Pathology and Deep Learning
This course will be held online until the coronavirus pandemic is contained to such an extent that the Bavarian state government can allow face-to-face teaching again.
- Tue 16:30-18:00, Room 02.133-113