3 papers
eess.IV2025
subCellSAM: Zero-Shot (Sub-)Cellular Segmentation for Hit Validation in Drug Discovery
Jacob Hanimann, Daniel Siegismund, Mario Wieser +1
High-throughput screening using automated microscopes is a key driver in biopharma drug discovery, enabling the parallel evaluation of thousands of drug candidates for diseases suc…
cs.CV2024
PCIM: Learning Pixel Attributions via Pixel-wise Channel Isolation Mixing in High Content Imaging
Daniel Siegismund, Mario Wieser, Stephan Heyse +1
Deep Neural Networks (DNNs) have shown remarkable success in various computer vision tasks. However, their black-box nature often leads to difficulty in interpreting their decision…
cs.CV2023
Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing
Daniel Siegismund, Mario Wieser, Stephan Heyse +1
Uncovering novel drug candidates for treating complex diseases remain one of the most challenging tasks in early discovery research. To tackle this challenge, biopharma research es…