Jürgen W. Czarske

This study uses generative adversarial networks to perform virtual staining of osteoclast cultures, showing that input image background influences staining predictions and enabling non-invasive analysis.

This study evaluates how hyperparameters and model versions affect deep learning-based tracking of microrobots in phantom tissue, finding that YOLOv9 outperforms YOLOv8 and adjusting loss functions improves performance.

This paper improves the spatial resolution of impulsive stimulated Brillouin scattering microscopy by optimizing excitation parameters and using a noise suppressing window function, achieving a fast 3D imaging rate.

The paper develops a holographic optogenetic platform to study long-term functional connectivity in human stem-cell-derived neuronal networks.