Fast and robust multiplane single-molecule localization microscopy using a deep neural network
Fast and robust multiplane single-molecule localization microscopy using a deep neural network
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使用深度神经网络的快速、鲁棒的多平面单分子定位显微镜
DOI：
10.1016/j.neucom.2021.04.050
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发表时间：
2021
期刊：
影响因子：
6
通讯作者：
Murata Noboru
中科院分区：
文献类型：
--
作者：
Aritake Toshimitsu;Hino Hideitsu;Namiki Shigeyuki;Asanuma Daisuke;Hirose Kenzo;Murata Noboru
单分子定位显微术是生物学研究中广泛使用的技术，用于测量小于衍射极限的样品的纳米结构。本研究使用多焦平面显微镜和解决的三维（3D）单分子定位问题，其中分子的横向和轴向位置估计。然而，当使用多焦平面显微镜，三维定位的估计精度很容易恶化的相机位置的小的横向漂移。沿着提出了一个三维分子定位问题，并将横向漂移估计作为一个压缩感知问题。深度神经网络（DNN）被用来准确有效地解决这个问题。结果表明，该方法对横向漂移具有较强的鲁棒性，在不进行明显漂移校正的情况下，可实现横向20 nm、轴向50 nm的精度。
Single-molecule localization microscopy is a widely used technique in biological research for measuring the nanostructures of samples smaller than the diffraction limit. This study uses multifocal plane microscopy and addresses the three-dimensional (3D) single-molecule localization problem, where lateral and axial locations of molecules are estimated. However, when multifocal plane microscopy is used, the estimation accuracy of 3D localization is easily deteriorated by the small lateral drifts of camera positions. A 3D molecule localization problem was presented along with the lateral drift estimation as a compressed sensing problem. A deep neural network (DNN) was applied to solve this problem accurately and efficiently. The results show that the proposed method is robust to lateral drift and achieves an accuracy of 20 nm laterally and 50 nm axially without an explicit drift correction.