Shuang Bo, Wang Wenxiao, Shen Hao, Tauzin Lawrence J, Flatebo Charlotte, Chen Jianbo, Moringo Nicholas A, Bishop Logan D C, Kelly Kevin F, Landes Christy F
Department of Chemistry, Rice University, Houston, TX 77251, USA.
Department of Electrical and Computer Engineering, Rice University, Houston, TX 77251, USA.
Sci Rep. 2016 Aug 4;6:30826. doi: 10.1038/srep30826.
Super-resolution microscopy with phase masks is a promising technique for 3D imaging and tracking. Due to the complexity of the resultant point spread functions, generalized recovery algorithms are still missing. We introduce a 3D super-resolution recovery algorithm that works for a variety of phase masks generating 3D point spread functions. A fast deconvolution process generates initial guesses, which are further refined by least squares fitting. Overfitting is suppressed using a machine learning determined threshold. Preliminary results on experimental data show that our algorithm can be used to super-localize 3D adsorption events within a porous polymer film and is useful for evaluating potential phase masks. Finally, we demonstrate that parallel computation on graphics processing units can reduce the processing time required for 3D recovery. Simulations reveal that, through desktop parallelization, the ultimate limit of real-time processing is possible. Our program is the first open source recovery program for generalized 3D recovery using rotating point spread functions.
使用相位掩膜的超分辨率显微镜是一种用于三维成像和跟踪的很有前景的技术。由于所得点扩散函数的复杂性，通用的恢复算法仍然缺失。我们引入了一种三维超分辨率恢复算法，该算法适用于生成三维点扩散函数的各种相位掩膜。快速去卷积过程生成初始猜测值，然后通过最小二乘法拟合进一步优化。使用机器学习确定的阈值抑制过拟合。对实验数据的初步结果表明，我们的算法可用于在多孔聚合物薄膜内对三维吸附事件进行超定位，并且对于评估潜在的相位掩膜很有用。最后，我们证明在图形处理单元上进行并行计算可以减少三维恢复所需的处理时间。模拟结果表明，通过桌面并行化，实现实时处理的最终极限是可能的。我们的程序是第一个用于使用旋转点扩散函数进行通用三维恢复的开源恢复程序。
