An LED-Based structured illumination microscope using a digital micromirror device and GPU accelerated image reconstruction

Musa Aydin; Yiǧit Uysalli; Ekin Özgönül; Berna Morova; Fatmanur Tiryaki; Elif Nur Firat-Karalar; Buket Doǧan; Alper Kiraz

doi:10.1371/journal.pone.0273990

An LED-Based structured illumination microscope using a digital micromirror device and GPU accelerated image reconstruction

Musa Aydin^*, Yiǧit Uysalli, Ekin Özgönül, Berna Morova, Fatmanur Tiryaki, Elif Nur Firat-Karalar, Buket Doǧan, Alper Kiraz^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

When combined with computational approaches, fluorescence imaging becomes one of the most powerful tools in biomedical research. It is possible to achieve resolution figures beyond the diffraction limit, and improve the performance and flexibility of high-resolution imaging systems with techniques such as structured illumination microscopy (SIM) reconstruction. In this study, the hardware and software implementation of an LED-based superresolution imaging system using SIM employing GPU accelerated parallel image reconstruction is presented. The sample is illuminated with two-dimensional sinusoidal patterns with various orientations and lateral phase shifts generated using a digital micromirror device (DMD). SIM reconstruction is carried out in frequency space using parallel CUDA kernel functions. Furthermore, a general purpose toolbox for the parallel image reconstruction algorithm and an infrastructure that allows all users to perform parallel operations on images without developing any CUDA kernel code is presented. The developed image reconstruction algorithm was run separately on a CPU and a GPU. Two different SIM reconstruction algorithms have been developed for the CPU as mono-thread CPU algorithm and multi-thread OpenMP CPU algorithm. SIM reconstruction of 1024 × 1024 px images was achieved in 1.49 s using GPU computation, indicating an enhancement by*28 and*20 in computation time when compared with mono-thread CPU computation and multi-thread OpenMP CPU computation, respectively.

Original language	English
Article number	e0273990
Journal	PLoS ONE
Volume	17
Issue number	9 September
DOIs	https://doi.org/10.1371/journal.pone.0273990
Publication status	Published - Sept 2022
Externally published	Yes

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Publisher Copyright:
© 2022 Aydin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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title = "An LED-Based structured illumination microscope using a digital micromirror device and GPU accelerated image reconstruction",

abstract = "When combined with computational approaches, fluorescence imaging becomes one of the most powerful tools in biomedical research. It is possible to achieve resolution figures beyond the diffraction limit, and improve the performance and flexibility of high-resolution imaging systems with techniques such as structured illumination microscopy (SIM) reconstruction. In this study, the hardware and software implementation of an LED-based superresolution imaging system using SIM employing GPU accelerated parallel image reconstruction is presented. The sample is illuminated with two-dimensional sinusoidal patterns with various orientations and lateral phase shifts generated using a digital micromirror device (DMD). SIM reconstruction is carried out in frequency space using parallel CUDA kernel functions. Furthermore, a general purpose toolbox for the parallel image reconstruction algorithm and an infrastructure that allows all users to perform parallel operations on images without developing any CUDA kernel code is presented. The developed image reconstruction algorithm was run separately on a CPU and a GPU. Two different SIM reconstruction algorithms have been developed for the CPU as mono-thread CPU algorithm and multi-thread OpenMP CPU algorithm. SIM reconstruction of 1024 × 1024 px images was achieved in 1.49 s using GPU computation, indicating an enhancement by*28 and*20 in computation time when compared with mono-thread CPU computation and multi-thread OpenMP CPU computation, respectively.",

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AU - Özgönül, Ekin

AU - Morova, Berna

AU - Tiryaki, Fatmanur

AU - Firat-Karalar, Elif Nur

AU - Doǧan, Buket

AU - Kiraz, Alper

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An LED-Based structured illumination microscope using a digital micromirror device and GPU accelerated image reconstruction

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