@inproceedings{48ed6ab25a8845a0911bd35d42860d0a,
title = "High-speed image reconstruction for super-resolution structured illumination microscopy using facile optimization and conversion of reconstruction code in the GPU environment",
abstract = "Super-resolution, structured illumination microscopy (SIM) is an ideal modality for imaging live cells due to its relatively high speed and low photon-induced damage to the cells. SIM consists of two generic components: (i) sample illumination by a sinusoidal pattern and (ii) computational reconstruction of a super-resolution image. The rate-limiting step in observing a super-resolution image in SIM is the reconstruction speed of the algorithm required to form a single image from as many as nine raw images. These reconstruction algorithms impose a significant computing burden due to a complex workflow and a large number of calculations requiring 10-300 seconds per image nullifying real-time imaging. In this mini-review, we show how the approaches we developed to improve Hessian-SIM algorithm reconstruction speed can be used to improve other SIM image reconstruction algorithms. These approaches, which included code improvement, conversion to the GPU environment, and use of cost-effective high-performance computers produce up to 500-fold increases in image reconstruction speed.",
keywords = "CPU, GPU, image reconstruction, structured illumination microscopy, super-resolution imaging",
author = "Kwangsung Oh and Bianco, {Piero R.}",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; SPIE-CLP Conference on Advanced Photonics 2023 ; Conference date: 22-08-2023 Through 23-08-2023",
year = "2023",
doi = "10.1117/12.2689967",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Zayats, {Anatoly V.} and Xiao-Cong Yuan",
booktitle = "SPIE-CLP Conference on Advanced Photonics 2023",
}