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| Artificial Intelligence in BioMedical Image Analysis (AIBIA)
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Project Description:
The WISS2025 Research and Transfer Lab on Artificial Intelligence in BioMedical Image Analysis (AIBIA) is devoted
to interdisciplinary, AI-oriented research in the area of Life Sciences, in particular with Salzburg based clinical and
(bio)medical research groups. The aim is to identify fruitful collaboration fields for joint research in computer vision, initiating
high potential collaborations and subsequent scientific publications. The mid-term aim is to establish sustainable collaboration areas
and human resources capable of advancing this type of interdisciplinary research in the Salzburg region.
Life Science cooperation partners come from the Salzburg University Hospital (SALK), the Paracelsus Medical University (PMU), and from the Department of Biosciences and Medical Biology
at the University of Salzburg (PLUS).
This project is conducted in
collaboration with Stefan Wegenkittl and Michael Gadermayr, both
from the Department Information Technologies and Digitalisation at the Salzburg University of Applied Sciences.
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Members:
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Timeframe:
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Publications:
- [Wimmer26a
] Medical image annotations for AI-based wound segmentation - the rocky road to high-quality training data Georg Wimmer, Christof Kauba, Christian Puttinger, Pamina Schlager, Roland Zauner, Carolin Gemeier, Tobias Welponer, Christine Prodinger, Anja Diem, Katharina Ude-Schoder, Martin Laimer, Johann W. Bauer, Andreas Uhl In Bildverarbeitung für die Medizin 2026, pp. 299-306, Informatik Aktuell, Springer Vieweg, Wiesbaden, 2026
- [Xin26a
] Towards a Visual Distinction of Benign and Tumorous Wound Surface in Epidermolysis Bullosa Ding Xin, Verena Wally, Christina Guttmann-Gruber, Bernadette Liemberger, Johann Bauer, Andreas Uhl In Bildverarbeitung für die Medizin 2026, pp. 195-202, Informatik Aktuell, Springer Vieweg, Wiesbaden, 2026
- [Wimmer25a
] Microglia cell segmentation using a hand-crafted method capable of handling high noise levels in image data Georg Wimmer, Ibrahim Khan, Lara Bieler, Bruno Benedetti, Sebastien Couillard-Despres, Andreas Uhl In 15th Eurographics Symposium on Visual Computing for Biology and Medicine (VCBM'25)The Eurographics Association, 2025
- [Schuiki25b
] Quantifying Inter-annotator Agreement and Generalist Model Limitations in Imaging Mass Cytometry Single Cell Segmentation Johannes Schuiki, Markus Steiner, Heinz Hofbauer, Stephan Drothler, Giulia Pessina, Richard Greil, Nadja Zaborsky, Andreas Uhl In Sharib Ali, David C. Hogg, Michelle Peckham, editors, Medical Image Understanding and Analysis, pp. 146-159, Leeds, UK, Lecture Notes in Computer Science, 15918, Springer Nature Switzerland, July 15 - July 17, 2025
- [Schuiki25a
] Intrinsic Correspondence of Classification Ground Truth and Image Content on the Example of Endoscopic Images Johannes Schuiki, Andreas Uhl In Bildverarbeitung für die Medizin 2025, pp. 209-214, Regensburg, Germany, Springer Fachmedien Wiesbaden, March 9 - March 11, 2025
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