Automatic tracking of proteins in sequences of fluorescence images
Retinal Vein Occlusion
The development of digital microscopy and computational power is providing new opportunities for analyzing the motility of the vesicles (proteins) within living cells. In this paper, an automatic method is developed to segment and track vesicles in large amount of fluorescence images, in order to compute a number of quantitative parameters such as displacement, residence time, binding, or immobile fraction. We present a method that permits the automatic tracking of subcellular structures in long sequences of fluorescence images (up to 100 frames). The method we propose has been tested on 92 data sets totaling 8225 frames.