Single-molecule localization by voxel-wise regression using convolutional neural network
Aritake, T., Hino, H., Namiki, S., Asanuma, D., Hirose, K., Murata, N. Results in Optics Volume 1, November 2020, 100019 https://doi.org/10.1016/j.rio.2020.100019
Single‐molecule localization microscopy is widely used in biological research for measuring the nanostructures of samples smaller than the diffraction limit. In this paper, a novel method for regression of the coordinates of molecules for multifocal plane microscopy is presented. A regression problem for the target space is decomposed into regression problems for small subsets of the target space. Then, a deep neural network is used to solve these problems. By decomposing the regression problem, a fully convolutional neural network can be used to solve the regression problems. The computation of the network is efficient, and a simple and parameter‐free loss function can be used to train the network. The proposed algorithm is validated by both simulated and real data obtained by quad‐plane microscopy.