Adaptive Spatio-Temporal Restoration for 4D Fluorescence Microscopic Imaging

We present a spatio-temporal filtering method for significantly increasing the signal-to-noise ratio (SNR) in noisy fluorescence microscopic image sequences where small particles have to be tracked from frame to frame. Image sequence restoration is achieved using a statistical approach involving an appropriate on-line window geometry specification. We have applied this method to noisy synthetic and real microscopic image sequences where a large number of small fluorescently labeled vesicles are moving in regions close to the Golgi apparatus. The SNR is shown to be drastically improved and the enhanced vesicles can be segmented. This novel approach can be further exploited for biological studies where the dynamics of small objects of interest have to be analyzed in molecular and sub-cellular bio-imaging.