图形处理器上高斯光斑的最小二乘拟合
Least-squares fitting of Gaussian spots on graphics processing units
摘要：
空间分辨率在纳米范围内的样品的研究依赖于样品的精确和稳定定位。由于光学显微镜中典型样品台固有的机械不稳定性，通常需要在采集期间控制和/或监测样品位置。以高速跟踪稀疏分布的基准标记允许以毫秒时间尺度稳定样品位置。为此，我们提出了一种可扩展的拟合算法，与Gpufit相比，二维高斯拟合的性能有显着提高。
英文摘要：
The investigation of samples with a spatial resolution in the nanometer range relies on the precise and stable positioning of the sample. Due to inherent mechanical instabilities of typical sample stages in optical microscopes, it is usually required to control and/or monitor the sample position during the acquisition. The tracking of sparsely distributed fiducial markers at high speed allows stabilizing the sample position at millisecond time scales. For this purpose, we present a scalable fitting algorithm with significantly improved performance for two-dimensional Gaussian fits as compared to Gpufit.
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