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Fluorescence microscopy has allowed studying dynamical biological processes in vivo with an ever increasing accuracy. Nonetheless, the physically inherent resolution limits impede the study of very dynamical intracellular processes such as microtubule dynamics. One way to overcome this limited resolution is to reconstruct the underlying object dynamics from the image data by using Bayesian statistics...
Simulating synthetic image data is crucial for the design and validation of bio-imaging pipelines. Most of the existing frameworks assume objects in pixel space, whereas most of the spatio-temporal models of biological processes are formulated in object space. We show that the key to a physically-principled synthetic image data simulation engine is to model carefully the mapping between objects and...
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