Data fusion and smoothing for probabilistic tracking of viral structures in fluorescence microscopy images

Christian Ritter, Thomas Wollmann, Ji Young Lee, Andrea Imle, Barbara Müller, Oliver T. Fackler, Ralf Bartenschlager, Karl Rohr

Abstract: Highlights•Probabilistic particle tracking by multi-sensor data fusion and Bayesian smoothing.•Integration of multiple measurements from separate measurement processes.•Past and future information exploited by smoothing and covariance intersection.•Motion information employed in the cost function for correspondence finding.•Improved results for microscopy image data of different types of viruses.