论文标题
使用深神经网络的快速和健壮的多平台单分子定位显微镜
Fast and robust multiplane single molecule localization microscopy using deep neural network
论文作者
论文摘要
单分子定位显微镜被广泛用于生物学研究中，用于测量小于衍射极限的样品的纳米结构。这项研究使用多灶性平面显微镜并解决了3D单分子定位问题，其中估计了分子的侧向和轴向位置。但是，当我们使用多灶性平面显微镜时，相机位置的小横向漂移很容易降低3D定位的估计精度。我们制定了一个3D分子定位问题，并将横向漂移作为压缩感应问题的估计，将深层神经网络应用于准确有效地解决此问题。所提出的方法对横向漂移是可靠的，并在轴向上达到20 nm的精度，并且在没有明确的漂移校正的情况下轴向上的50 nm。
Single molecule localization microscopy is widely used in biological research for measuring the nanostructures of samples smaller than the diffraction limit. This study uses multifocal plane microscopy and addresses the 3D single molecule localization problem, where lateral and axial locations of molecules are estimated. However, when we multifocal plane microscopy is used, the estimation accuracy of 3D localization is easily deteriorated by the small lateral drifts of camera positions. We formulate a 3D molecule localization problem along with the estimation of the lateral drifts as a compressed sensing problem, A deep neural network was applied to accurately and efficiently solve this problem. The proposed method is robust to the lateral drifts and achieves an accuracy of 20 nm laterally and 50 nm axially without an explicit drift correction.
