A parameter-optimizing model-based approach to the analysis of low-SNR image sequences for biological virus detection

Dominic Siedhoff
This thesis presents the multi-objective parameter optimization of a novel image analysis process. The focus of application is automatic detection of nano-objects, for example biological viruses, in real-time. Nano-objects are detected by analyzing time series of images recorded with the PAMONO biosensor, after parameters have been optimized on synthetic data created by a signal model for PAMONO. PAMONO, which is short for Plasmon-Assisted Microscopy of Nano-Sized Objects, is a biosensor yielding indirect proofs for objects...
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