Histogram clustering for rapid time-domain fluorescence lifetime image analysis
Li, Yahui and Sapermsap, Natakorn and Yu, Jun and Tian, Jinshou and Chen, Yu and Li, David Day-Uei (2021) Histogram clustering for rapid time-domain fluorescence lifetime image analysis. Biomedical Optics Express, 12 (7). pp. 4293-4307. ISSN 2156-7085 (https://doi.org/10.1364/BOE.427532)
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Abstract
We propose a histogram classification (HC) method to accelerate fluorescence lifetime imaging (FLIM) analysis in pixel-wise and global fitting modes. The proposed method’s principle was demonstrated, and the combinations of HC with traditional FLIM analysis were explained. We assessed HC methods with both simulated and experimental datasets. The results reveal that HC not only increases analysis speed (up to 106 times) but also enhances lifetime estimation accuracy. Fast lifetime analysis strategies were suggested with execution times around or below 30 us per histograms on MATLAB R2016a, 64-bit with the Intel(R) Celeron(R) CPU (2950M @ 2GHz).
ORCID iDs
Li, Yahui, Sapermsap, Natakorn, Yu, Jun![ORCID logo](/images/orcid_16x16.png)
![ORCID logo](/images/orcid_16x16.png)
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Item type: Article ID code: 76715 Dates: DateEvent21 June 2021Published8 June 2021Accepted10 April 2021SubmittedSubjects: Science > Physics > Optics. Light Department: Faculty of Science > Physics
Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences
Strategic Research Themes > Health and Wellbeing
Technology and Innovation Centre > Bionanotechnology
Faculty of Engineering > Biomedical EngineeringDepositing user: Pure Administrator Date deposited: 09 Jun 2021 08:58 Last modified: 04 Sep 2024 01:11 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/76715