Tracking Single Quantum Dots in Live Cells with Minimal Paths

We present here a novel method for automatically detecting and tracking semi-conductor quantum dots (QDs) in sequences of fluorescence images. QDs are new nanometersized fluorescent probes with great prospects for ultrasensitive biological imaging. When specifically attached to a biomolecule, they can be observed and tracked in live cells at the single molecule level over unprecedented durations. Due to QD complex optical properties, such as fluorescence intermittency, the quantitative analysis of image stacks is however challenging and requires advanced algorithms. Our tracking approach, instead of a frame by frame analysis, is based on perceptual grouping in a spatio-temporal volume. By applying a detection process based on an image fluorescence model, we first obtain a set of unstructured points. Individual molecular trajectories are then considered as minimal paths in a Riemannian metric derived from the fluorescence image stack. These paths are computed with the Fast Marching method, and few parameters are required. We illustrate our approach by showing experimental results issued from the tracking of individual glycine receptors in the membrane of live neurons.

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