Project: High-Throughput Computational and Data Pipeline for iSCAT Microscopy
Description
Interferometric scattering (iSCAT) microscopy is a technique to detect small particles (like individual proteins or live viruses) by capturing the interference between scattered light and a reference reflection. Currently, a major bottleneck is computational: there is a need for an end-to-end data streaming architecture to process the high-bandwidth raw video streams from the measurement devices and to obtain a high-performance queryable database of particle trajectories.
This project includes implementing GPU-accelerated algorithms for sub-pixel 2D localization of interference patterns and implementing multi-object tracking to reconstruct these particle trajectories. These interference patterns encode 3D spatial data and physical properties which must be extracted with high precision.
This project also includes designing and implementing a suitable data management solution to query the large amount of data, including the raw video and the derived time-series trajectories and physical metadata. This project is in close coorperation with physicists.
Details
- Supervisor
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Robert Brijder
- Secondary supervisor
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AKAnna Kashkanova
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