Evidence map›Paper›PMID 36084054›Full record

ArticlePloS one2022

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

Musa Aydın, Yiğit Uysallı, Ekin Özgönül, Berna Morova, Fatmanur Tiryaki, Elif Nur Firat-Karalar, Buket Doğan, Alper Kiraz

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.8field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Musa AydınDepartment of Computer Engineering, Fatih Sultan Mehmet Vakif University, Istanbul, Turkey.ORCID 0000-0002-5825-2230
Yiğit UysallıDepartment of Physics, Koç University, Istanbul, Turkey.
Ekin ÖzgönülDepartment of Physics, Koç University, Istanbul, Turkey.ORCID 0000-0003-2091-7572
Berna MorovaDepartment of Physics, Koç University, Istanbul, Turkey.
Fatmanur TiryakiDepartment of Molecular Biology and Genetics, Koç University, Istanbul, Turkey.
Elif Nur Firat-KaralarDepartment of Molecular Biology and Genetics, Koç University, Istanbul, Turkey.
Buket DoğanDepartment of Computer Engineering, Marmara University, Istanbul, Turkey.
Alper KirazDepartment of Physics, Koç University, Istanbul, Turkey.ORCID 0000-0001-7977-1286
Koç University · TRFatih Sultan Mehmet Waqf University · TRMarmara University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 super-resolution 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.

Indexed as

LightingMicroscopyAlgorithmsImage Processing, Computer-AssistedSoftware

Identifiers

PMID36084054
PMCPMC9462783
OpenAlexW4295047694

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.