Our lab has built a microscope for recording the behavior of individual Caenorhabditis elegans over the course of weeks. In order to analyze the raw images, we developed software which combines cutting-edge deep learning with classical image processing for optimal results. Specifically, our software enhances the Segment and Track Anything Model (SAM) by integrating background subtraction to improve the segmentation and tracking of worms.
- Field: Biophysics
- Laboratory: Laboratory of the Physics of Biological Systems (SB-LPBS)
- Project leader: Sahand Rahi
- Budget: 30’000.00 CHF