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Robust online image processing for high-throughput super-resolution localization microscopy

机译:高吞吐量超分辨率定位显微镜的强大在线图像处理

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Super-resolution localization microscopy is a powerful tool to visualize molecular structures at a nanoscale resolution.High-density emitter localization combined with a large field of view and fast imaging frame rate is an effective strategyto achieve a high throughput. But the complex algorithms used to precisely localize the overlapping molecules in denseemitter scenarios limits their usage to mostly small image size. Here we present a computationally simple non-iterativemethod for high-density emitter localization to enable online image processing that remains robust even for low signalsand heterogeneous background. Through numerical simulation and biological experiments, we demonstrate that ourapproach improves the computation speed by two orders of magnitude on CPU and three orders of magnitude upon GPUacceleration to realize online image processing, without compromising localization accuracy for various imagecharacteristics.
机译:超分辨率定位显微镜是一种强大的工具,可在纳米级分辨率下可视化分子结构。高密度发射器定位与大视野相结合,快速成像帧速率是一种有效的策略实现高吞吐量。但是,复杂的算法用于精确地将重叠分子精确定位密集的发射器方案将其用法限制为大多数小图像尺寸。在这里,我们提出了一种计算简单的非迭代高密度发射器定位的方法,使在线图像处理甚至用于低信号仍然坚固和异质背景。通过数值模拟和生物实验,我们证明了我们的方法通过CPU上的两个数量级和GPU级的三个数量级来提高计算速度加速来实现在线图像处理,而不影响各种图像的本地化精度特征。

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