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Fluorescence time-lapse microscopy is a powerful technique for observing the spatial-temporal behavior of viruses. To quantitatively analyze the exhibited dynamical relationships, tracking of viruses over time is required. We have developed probabilistic approaches based on particle filters for tracking multiple virus particles in time-lapse fluorescence microscopy images. We employ a mixture of particle...
Modern developments in time-lapse microscopy enable the observation of a variety of processes exhibited by viruses. The dynamic nature of these processes requires the tracking of viruses over time to explore the spatio-temporal relationships. In this work, we developed deterministic and probabilistic approaches for multiple virus tracking. A quantitative comparison based on synthetic image sequences...
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