Fast image scanning microscopy with efficient image reconstruction

Abstract

Image Scanning Microscopy is an advanced linear super-resolution fluorescence microscopy technique. Unlike traditional methods that introduce complex optical system designs, ISM is capble of taking the advantage of computational method to achieve super-resolution. As ISM involves large-scale localizations to all scanned-positions in most experiments, robust and accurate algorithms are required to avoid artifacts. Meanwhile, the existing ISM image reconstruction method is mainly based on post-processing technique due to high computing complexity. Therefore, large-scale images processing in ISM image reconstruction becomes too computationally intensive, which impedes the development of fast ISM. In this article, a robust ISM scanning-position localization technique and an efficient accurate image reconstruction technique for large scale ISM reconstruction are proposed. In particular, the localization of the ISM scanning position is realized by efficient image correlation and accurate robust Gaussian fitting. For simplicity and accuracy, the image reconstruction step introduces an efficient sub-pixel reassignment technique, by which image up-sampling is completely avoided. The simulation results show high performance in the proposed localization technique. The experimental result shows that the proposed image reconstruction technique can reach 20 times faster than existing method, which makes it very suitable for large-scale image processing in ISM image reconstruction, especially in a real-time ISM system.