activity
20222025
collaborators

7 papers

cs.CV2025

Decomposition Sampling for Efficient Region Annotations in Active Learning

Jingna Qiu, Frauke Wilm, Mathias Öttl +5

Active learning improves annotation efficiency by selecting the most informative samples for annotation and model training. While most prior work has focused on selecting informati…

cs.CV2025

Faster, Self-Supervised Super-Resolution for Anisotropic Multi-View MRI Using a Sparse Coordinate Loss

Maja Schlereth, Moritz Schillinger, Katharina Breininger

Acquiring images in high resolution is often a challenging task. Especially in the medical sector, image quality has to be balanced with acquisition time and patient comfort. To st…

cs.CV2024

Leveraging image captions for selective whole slide image annotation

Jingna Qiu, Marc Aubreville, Frauke Wilm +4

Acquiring annotations for whole slide images (WSIs)-based deep learning tasks, such as creating tissue segmentation masks or detecting mitotic figures, is a laborious process due t…

eess.IV2023

Focus on Content not Noise: Improving Image Generation for Nuclei Segmentation by Suppressing Steganography in CycleGAN

Jonas Utz, Tobias Weise, Maja Schlereth +5

Annotating nuclei in microscopy images for the training of neural networks is a laborious task that requires expert knowledge and suffers from inter- and intra-rater variability, e…

cs.CV2023

Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation

Jingna Qiu, Frauke Wilm, Mathias Öttl +5

The process of annotating histological gigapixel-sized whole slide images (WSIs) at the pixel level for the purpose of training a supervised segmentation model is time-consuming. R…

eess.IV2022

Automatic Classification of Neuromuscular Diseases in Children Using Photoacoustic Imaging

Maja Schlereth, Daniel Stromer, Katharina Breininger +4

Neuromuscular diseases (NMDs) cause a significant burden for both healthcare systems and society. They can lead to severe progressive muscle weakness, muscle degeneration, contract…

eess.IV2022

Initial Investigations Towards Non-invasive Monitoring of Chronic Wound Healing Using Deep Learning and Ultrasound Imaging

Maja Schlereth, Daniel Stromer, Yash Mantri +6

Chronic wounds including diabetic and arterial/venous insufficiency injuries have become a major burden for healthcare systems worldwide. Demographic changes suggest that wound car…