Jonathan Ganz

My name is Jonathan Ganz and I am a PhD student at the Ingolstadt University of Applied Sciences. I received my bachelor’s and master’s degrees in medical engineering from the University of Applied Sciences Trier. Besides my general interest in deep learning and medical image understanding, my research focuses on the assessment of global and local information from histology slides using deep learning.

Publications:

Aubreville, M., Ganz, J., Ammeling, J., Kaltenecker, C., & Bertram, C. A. (2024, July 3). Model-based Cleaning of the QUILT-1M Pathology Dataset for Text-Conditional Image Synthesis. Medical Imaging with Deep Learning. Medical Imaging with Deep Learning, Paris, France. https://openreview.net/forum?id=m7wYKrUjzV Cite

Aubreville, M., Stathonikos, N., Donovan, T. A., Klopfleisch, R., Ammeling, J., Ganz, J., Wilm, F., Veta, M., Jabari, S., Eckstein, M., Annuscheit, J., Krumnow, C., Bozaba, E., Çayır, S., Gu, H., Chen, X. ‘Anthony,’ Jahanifar, M., Shephard, A., Kondo, S., … Bertram, C. A. (2024). Domain generalization across tumor types, laboratories, and species — Insights from the 2022 edition of the Mitosis Domain Generalization Challenge. Medical Image Analysis, 94, 103155. https://doi.org/10.1016/j.media.2024.103155 Cite

Aubreville, M., Pan, Z., Sievert, M., Ammeling, J., Ganz, J., Oetter, N., Stelzle, F., Frenken, A.-K., Breininger, K., & Goncalves, M. (2024). Few Shot Learning for the Classification of Confocal Laser Endomicroscopy Images of Head and Neck Tumors. In A. Maier, T. M. Deserno, H. Handels, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024 (pp. 143–148). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-44037-4_42 Cite

Ammeling, J., Hecker, M., Ganz, J., Donovan, T. A., Klopfleisch, R., Bertram, C. A., Breininger, K., & Aubreville, M. (2024). Automated Mitotic Index Calculation via Deep Learning and Immunohistochemistry. In A. Maier, T. M. Deserno, H. Handels, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024 (pp. 123–128). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-44037-4_37 Cite

Ganz, J., Puget, C., Ammeling, J., Parlak, E., Kiupel, M., Bertram, C. A., Breininger, K., Klopfleisch, R., & Aubreville, M. (2024). Assessment of Scanner Domain Shifts in Deep Multiple Instance Learning. In A. Maier, T. M. Deserno, H. Handels, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2024 (pp. 137–142). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-44037-4_41 Cite

Ammeling, J., Manger, C., Kwaka, E., Krügel, S., Uhl, M., Kießig, A., Fritz, A., Ganz, J., Riener, A., Bertram, C. A., Breininger, K., & Aubreville, M. (2023). Appealing but Potentially Biasing – Investigation of the Visual Representation of Segmentation Predictions by AI Recommender Systems for Medical Decision Making. MuC ’23: Mensch Und Computer 2023, 330–335. https://doi.org/10.1145/3603555.3608561 Cite

Aubreville, M., Wilm, F., Stathonikos, N., Breininger, K., Donovan, T. A., Jabari, S., Veta, M., Ganz, J., Ammeling, J., Van Diest, P. J., Klopfleisch, R., & Bertram, C. A. (2023). A comprehensive multi-domain dataset for mitotic figure detection. Scientific Data, 10(1), 484. https://doi.org/10.1038/s41597-023-02327-4 Cite Download

Ammeling, J., Wilm, F., Ganz, J., Breininger, K., & Aubreville, M. (2023). Reference Algorithms for the Mitosis Domain Generalization (MIDOG) 2022 Challenge. In B. Sheng & M. Aubreville (Eds.), Mitosis Domain Generalization and Diabetic Retinopathy Analysis (Vol. 13597, pp. 201–205). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-33658-4_19 Cite

Ammeling, J., Schmidt, L.-H., Ganz, J., Niedermair, T., Brochhausen-Delius, C., Schulz, C., Breininger, K., & Aubreville, M. (2023). Attention-based Multiple Instance Learning for Survival Prediction on Lung Cancer Tissue Microarrays. In T. M. Deserno, H. Handels, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2023 (pp. 220–225). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-41657-7_48 Cite Download

Aubreville, M., Ganz, J., Ammeling, J., Donovan, T. A., Fick, R. Hj., Breininger, K., & Bertram, C. A. (2023). Deep Learning-based Subtyping of Atypical and Normal Mitoses using a Hierarchical Anchor-free Object Detector. In T. M. Deserno, H. Handels, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2023 (pp. 189–195). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-41657-7_40 Cite Download

Ganz, J., Lipnik, K., Ammeling, J., Richter, B., Puget, C., Parlak, E., Diehl, L., Klopfleisch, R., Donovan, T. A., Kiupel, M., Bertram, C. A., Breininger, K., & Aubreville, M. (2023). Deep Learning-based Automatic Assessment of AgNOR-scores in Histopathology Images. In T. M. Deserno, H. Handels, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2023 (pp. 226–231). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-41657-7_49 Cite Download

Ganz, J., Bertram, C. A., Klopfleisch, R., Jabari, S., Breininger, K., & Aubreville, M. (2022). Classification of visibility in multi-stain microscopy images. Medical Imaging with Deep Learning 2022. Cite Download

Ganz, J., Kirsch, T., Hoffmann, L., Bertram, C. A., Hoffmann, C., Maier, A., Breininger, K., Blümcke, I., Jabari, S., & Aubreville, M. (2021). Automatic and explainable grading of meningiomas from histopathology images. 69–80. https://proceedings.mlr.press/v156/ganz21a/ganz21a.pdf Cite Download