no code implementations • 8 Dec 2023 • Ribana Roscher, Marc Rußwurm, Caroline Gevaert, Michael Kampffmeyer, Jefersson A. dos Santos, Maria Vakalopoulou, Ronny Hänsch, Stine Hansen, Keiller Nogueira, Jonathan Prexl, Devis Tuia
These examples provide concrete steps to act on geospatial data with data-centric machine learning approaches.
1 code implementation • 2 Mar 2023 • Luca Tomasetti, Stine Hansen, Mahdieh Khanmohammadi, Kjersti Engan, Liv Jorunn Høllesli, Kathinka Dæhli Kurz, Michael Kampffmeyer
Precise ischemic lesion segmentation plays an essential role in improving diagnosis and treatment planning for ischemic stroke, one of the prevalent diseases with the highest mortality rate.
1 code implementation • 15 Oct 2022 • Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina MC Höhne, Michael Kampffmeyer
The need for interpretable models has fostered the development of self-explainable classifiers.
1 code implementation • 3 Mar 2022 • Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer
Motivated by this, and the observation that the foreground class (e. g., one organ) is relatively homogeneous, we propose a novel anomaly detection-inspired approach to few-shot medical image segmentation in which we refrain from modeling the background explicitly.
no code implementations • 10 Jan 2022 • Srishti Gautam, Marina M. -C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
The recent trend of integrating multi-source Chest X-Ray datasets to improve automated diagnostics raises concerns that models learn to exploit source-specific correlations to improve performance by recognizing the source domain of an image rather than the medical pathology.
no code implementations • 27 Aug 2021 • Srishti Gautam, Marina M. -C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
Current machine learning models have shown high efficiency in solving a wide variety of real-world problems.