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Tracking Single Quantum Dots in Live Cells with Minimal Paths

机译:以最小的路径追踪活细胞中的单个量子点

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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.
机译:我们在这里提出了一种自动检测和跟踪荧光图像序列中的半导体量子点(QDs)的新颖方法。 QD是新型纳米荧光探针,具有超灵敏生物成像的广阔前景。当与生物分子特异性结合时,它们可以在空前的持续时间内以单分子水平在活细胞中被观察和追踪。由于QD具有复杂的光学特性(例如荧光间歇性),因此图像堆栈的定量分析具有挑战性,并且需要先进的算法。我们的跟踪方法基于时空量的感知分组,而不是逐帧分析。通过应用基于图像荧光模型的检测过程,我们首先获得了一组非结构化点。然后,将单个分子轨迹视为源自荧光图像堆栈的黎曼度量中的最小路径。这些路径是使用快速行进方法计算的,几乎不需要任何参数。我们通过显示从活神经元膜中单个甘氨酸受体的跟踪中得出的实验结果来说明我们的方法。

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