Laser & Optoelectronics Progress, Volume. 60, Issue 2, 0230002(2023)

Smartphone-Based Snapshot Fluorescence Multispectral Imaging

Yuhao Li1,2, Yi Yu1、*, Zhiyuan Sun1, and Yuanchao Mu1,2
Author Affiliations
  • 1Fine Instrument and Equipment Research & Development Center, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, Jilin, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
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    Figures & Tables(10)
    Fluorescent color card
    Spectral intensity curves of 64 color blocks
    Smart phone and a homemade phone case (case with battery pack and fluorescent lamp)
    Comparison of initial and reconstructed fluorescence spectra of three representative fluorescent color patches in 31 bands. (a) Correlation coefficient is 0.9996 (maximum value); (b) correlation coefficient is 0.9384 (minimum value); (c) correlation coefficient is 0.9855 (close to average value)
    RGB mode autofluorescence images of the skin and oral cavity
    Reconstruction of multispectral autofluorescence data cube
    Spectral analysis and bacteria-targeted feature mapping
    Quantitative analysis of porphyrin and background autofluorescence produced by bacteria
    • Table 1. Correlation coefficient between initial and reconstructed fluorescence spectra of 64 color blocks

      View table

      Table 1. Correlation coefficient between initial and reconstructed fluorescence spectra of 64 color blocks

      0.9771

      0.9825

      0.9615

      0.9897

      0.9939

      0.9725

      0.9887

      0.9394

      0.9649

      0.9990

      0.9987

      0.9947

      0.9961

      0.9928

      0.9459

      0.9384

      0.9808

      0.9976

      0.9996

      0.9992

      0.9457

      0.9925

      0.9853

      0.9861

      0.9960

      0.9973

      0.9982

      0.9986

      0.9843

      0.9853

      0.9852

      0.9673

      0.9909

      0.9930

      0.9974

      0.9517

      0.9406

      0.9813

      0.9928

      0.9905

      0.9938

      0.9756

      0.9987

      0.9968

      0.9990

      0.9855

      0.9954

      0.9989

      0.9947

      0.9994

      0.9910

      0.9949

      0.9871

      0.9945

      0.9951

      0.9977

      0.9738

      0.9892

      0.9873

      0.9796

      0.9845

      0.9984

      0.9960

      0.9949

    • Table 2. Root mean square error between initial and reconstructed fluorescence spectra of 64 color blocks

      View table

      Table 2. Root mean square error between initial and reconstructed fluorescence spectra of 64 color blocks

      0.0373

      0.0448

      0.0876

      0.0560

      0.0352

      0.0414

      0.0593

      0.1263

      0.0552

      0.0226

      0.0459

      0.0459

      0.0250

      0.0251

      0.0676

      0.0294

      0.0514

      0.0354

      0.0349

      0.0211

      0.0574

      0.0436

      0.0304

      0.0836

      0.0384

      0.0555

      0.0380

      0.0759

      0.0574

      0.1514

      0.0403

      0.1240

      0.0440

      0.1266

      0.0306

      0.1822

      0.0847

      0.0705

      0.0382

      0.1253

      0.0506

      0.0718

      0.0338

      0.0396

      0.0426

      0.0327

      0.0388

      0.0518

      0.0755

      0.0876

      0.0850

      0.0478

      0.0729

      0.0547

      0.0814

      0.0525

      0.0480

      0.0356

      0.0469

      0.0451

      0.0589

      0.0231

      0.0453

      0.0524

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    Yuhao Li, Yi Yu, Zhiyuan Sun, Yuanchao Mu. Smartphone-Based Snapshot Fluorescence Multispectral Imaging[J]. Laser & Optoelectronics Progress, 2023, 60(2): 0230002

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    Paper Information

    Category: Spectroscopy

    Received: Jan. 10, 2022

    Accepted: Mar. 14, 2022

    Published Online: Feb. 7, 2023

    The Author Email: Yi Yu (13756006195@139.com)

    DOI:10.3788/LOP220491

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