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A Diffusion Model for Detecting and Classifying Vesicle Fusion and Undocking Events

Lorenz Berger, Majid Mirmehdi, Jeremy Tavare, Sam Reed, A Diffusion Model for Detecting and Classifying Vesicle Fusion and Undocking Events. Proceedings of the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2012), pp. II-321–328. October 2012. No electronic version available.

Abstract

Fluorescently-tagged proteins located on vesicles can fuse with the surface membrane (visualised as a `puff') or undock and return back into the bulk of the cell. Detection and quantitative measurement of these events from time-lapse videos has proven difficult. We propose a novel approach to detect fusion and undocking events by first searching for docked vesicles that `disappear' from the field of view, and then using a diffusion model to classify them as either fusion or undocking events. We can also use the same searching method to identify docking events. We present comparative results against existing algorithms.

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