1 code implementation • 11 Apr 2024 • Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Christopher C. Kaltenecker, Christof A. Bertram
The QUILT-1M dataset is the first openly available dataset containing images harvested from various online sources.
no code implementations • 19 Mar 2024 • Jonathan Ganz, Jonas Ammeling, Samir Jabari, Katharina Breininger, Marc Aubreville
We predicted the source patient of a slide with F1 scores of 50. 16 % and 52. 30 % on the LSCC and LUAD datasets, respectively, and with 62. 31 % on our meningioma dataset.
no code implementations • 2 Jan 2024 • Chloé Puget, Jonathan Ganz, Julian Ostermaier, Thomas Konrad, Eda Parlak, Christof Albert Bertram, Matti Kiupel, Katharina Breininger, Marc Aubreville, Robert Klopfleisch
This project aimed at training deep learning models (DLMs) to identify the c-Kit-11 mutational status of MCTs solely based on morphology without additional molecular analysis.
no code implementations • 15 Nov 2023 • Jonas Ammeling, Moritz Hecker, Jonathan Ganz, Taryn A. Donovan, Christof A. Bertram, Katharina Breininger, Marc Aubreville
The volume-corrected mitotic index (M/V-Index) was shown to provide prognostic value in invasive breast carcinomas.
no code implementations • 13 Nov 2023 • Marc Aubreville, Zhaoya Pan, Matti Sievert, Jonas Ammeling, Jonathan Ganz, Nicolai Oetter, Florian Stelzle, Ann-Kathrin Frenken, Katharina Breininger, Miguel Goncalves
This method is, in itself, an oversampling procedure, which has a relatively low sensitivity compared to the definitive tissue analysis on paraffin-embedded sections.
no code implementations • 27 Sep 2023 • Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan, Robert Klopfleisch, Jonathan Ganz, Jonas Ammeling, Frauke Wilm, Mitko Veta, Samir Jabari, Markus Eckstein, Jonas Annuscheit, Christian Krumnow, Engin Bozaba, Sercan Cayir, Hongyan Gu, Xiang 'Anthony' Chen, Mostafa Jahanifar, Adam Shephard, Satoshi Kondo, Satoshi Kasai, Sujatha Kotte, VG Saipradeep, Maxime W. Lafarge, Viktor H. Koelzer, Ziyue Wang, Yongbing Zhang, Sen yang, Xiyue Wang, Katharina Breininger, Christof A. Bertram
The challenge provided annotated histologic tumor images from six different domains and evaluated the algorithmic approaches for mitotic figure detection provided by nine challenge participants on ten independent domains.
no code implementations • 26 Sep 2023 • Andreas Haghofer, Eda Parlak, Alexander Bartel, Taryn A. Donovan, Charles-Antoine Assenmacher, Pompei Bolfa, Michael J. Dark, Andrea Fuchs-Baumgartinger, Andrea Klang, Kathrin Jäger, Robert Klopfleisch, Sophie Merz, Barbara Richter, F. Yvonne Schulman, Jonathan Ganz, Josef Scharinger, Marc Aubreville, Stephan M. Winkler, Matti Kiupel, Christof A. Bertram
Algorithmic morphometry was compared with karyomegaly estimates by 11 pathologists, manual nuclear morphometry of 12 cells by 9 pathologists, and the mitotic count as a benchmark.
1 code implementation • 15 Dec 2022 • Jonas Ammeling, Lars-Henning Schmidt, Jonathan Ganz, Tanja Niedermair, Christoph Brochhausen-Delius, Christian Schulz, Katharina Breininger, Marc Aubreville
Attention-based multiple instance learning (AMIL) algorithms have proven to be successful in utilizing gigapixel whole-slide images (WSIs) for a variety of different computational pathology tasks such as outcome prediction and cancer subtyping problems.
no code implementations • 15 Dec 2022 • Jonathan Ganz, Karoline Lipnik, Jonas Ammeling, Barbara Richter, Chloé Puget, Eda Parlak, Laura Diehl, Robert Klopfleisch, Taryn A. Donovan, Matti Kiupel, Christof A. Bertram, Katharina Breininger, Marc Aubreville
Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription.
1 code implementation • 12 Dec 2022 • Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Taryn A. Donovan, Rutger H. J. Fick, Katharina Breininger, Christof A. Bertram
In this work, we perform, for the first time, automatic subtyping of mitotic figures into normal and atypical categories according to characteristic morphological appearances of the different phases of mitosis.
1 code implementation • MICCAI Workshop COMPAY 2021 • Jonathan Ganz, Tobias Kirsch, Lucas Hoffmann, Christof A. Bertram, Christoph Hoffmann, Andreas Maier, Katharina Breininger, Ingmar Blümcke, Samir Jabari, Marc Aubreville
In a first approach, image patches are sampled from this region and regression is based on morphological features encoded by a ResNet-based network.