Publikationen

1997

• Environmental effects of energy use in the Baltic region.

  Morovic, T., & Tuschy, I. (1997). Environmental effects of energy use in the Baltic region. A sustainable Baltic Region, Bd. 2: Energy.

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    • Tuschy, Ilja

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  • 1997
  • Journal Article
  • • Tihomir Morovic
    • Ilja Tuschy

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• "Enabling Fast and Mobile Histopathology Image Annotation through Swipeable Interfaces SWAN"

  Banerjee, S. ". "Enabling Fast and Mobile Histopathology Image Annotation through Swipeable Interfaces SWAN". In H. " Handels, K. Breininger, T. Deserno, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Hrsg.), "Bildverarbeitung für die Medizin 2026" (S. 203–209). "Wiesbaden": "Springer Fachmedien Wiesbaden".

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  The annotation of large-scale histopathology image datasets remains a major bottleneck in developing robust deep learning models for clinically relevant tasks, such as mitotic figure classification. Folder-based annotation workflows are usually slow, fatiguing, and difficult to scale. To address these challenges, we introduce swipeable annotations (SWAN), an open-source, MIT-licensed web application that enables intuitive image patch classification using a swiping gesture. SWAN supports both desktop and mobile platforms, offers real-time metadata capture, and allows flexible mapping of swipe gestures to class labels. In a pilot study with four pathologists annotating 600 mitotic figure image patches,we compared SWANagainst a traditional folder-sorting workflow. SWAN enabled rapid annotations with pairwise percent agreement ranging from 86.52 \% to 93.68 \% (Cohen s $\kappa$ = 0.61—0.80), while for the folder-based method, the pairwise percent agreement ranged from 86.98 \% to 91.32 \% (Cohen s $\kappa$ = 0.63—0.75) for the task of classifying atypical versus normal mitotic figures, demonstrating high consistency between annotators and comparable performance. Participants rated the tool as highly usable and appreciated the ability to annotate on mobile devices. These results suggest that SWAN can accelerate image annotation while maintaining annotation quality, offering a scalable and user-friendly alternative to conventional workflows. The full codebase of the SWAN project, including analyses, can be found here: https://github.com/DeepMicroscopy/SWAN

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  • Conference Paper
  • • Sweta Banerjee
    • Heinz Handels
    • Katharina Breininger
    • Thomas Deserno
    • Andreas Maier
    • Klaus Maier-Hein
    • Christoph Palm
    • Thomas" Tolxdorff

• In .

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• Temperature influence on core losses and magnetization demand of electrical steel sheets using adapted Epstein frame and ring probe

  Regnet, M., Schäufele, T., Dietz, A., & Loehlein, B. Temperature influence on core losses and magnetization demand of electrical steel sheets using adapted Epstein frame and ring probe. In 13th International Electric Drives Production Conference (EDPC) (S. 1–7). http://doi.org/10.1109/EDPC60603.2023.10372149

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  • Conference Paper
  • • Martin Regnet
    • Thomas Schäufele
    • Armin Dietz
    • Bernd Loehlein