• Laser & Optoelectronics Progress
  • Vol. 56, Issue 6, 061005 (2019)
Fang Zhang1、2, Yue Wu1, Zhitao Xiao1、2、*, Lei Geng1、2, Jun Wu1、2, Yanbei Liu1、2, and Wen Wang1、2
Author Affiliations
  • 1 School of Electronics and Information Engineering, Tianjin Polytechnic University, Tianjin 300387, China
  • 2 Tianjin Key Laboratory of Optoelectronic Detection Technology and System, Tianjin 300387, China
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    DOI: 10.3788/LOP56.061005 Cite this Article Set citation alerts
    Fang Zhang, Yue Wu, Zhitao Xiao, Lei Geng, Jun Wu, Yanbei Liu, Wen Wang. Nanoparticle Segmentation Based on U-Net Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2019, 56(6): 061005 Copy Citation Text show less
    Spherical nanoparticle image taken by TEM and its partially enlarged view. (a) TEM image; (b) partially enlarged view
    Fig. 1. Spherical nanoparticle image taken by TEM and its partially enlarged view. (a) TEM image; (b) partially enlarged view
    Filtering results by partial differential equation. (a) Original nanoparticle image; (b) filtering result
    Fig. 2. Filtering results by partial differential equation. (a) Original nanoparticle image; (b) filtering result
    Network structure with BN
    Fig. 3. Network structure with BN
    Comparison chart of loss curves
    Fig. 4. Comparison chart of loss curves
    Comparison chart 1 of segmentation effect. (a) Level set algorithm; (b) PixelNet; (c) original U-Net; (d) improved network
    Fig. 5. Comparison chart 1 of segmentation effect. (a) Level set algorithm; (b) PixelNet; (c) original U-Net; (d) improved network
    Comparison chart 2 of segmentation effect. (a) Level set algorithm; (b) PixelNet; (c) original U-Net; (d) improved network
    Fig. 6. Comparison chart 2 of segmentation effect. (a) Level set algorithm; (b) PixelNet; (c) original U-Net; (d) improved network
    Comparison chart 3 of segmentation effect. (a) Level set algorithm; (b) PixelNet; (c) original U-Net; (d) improved network
    Fig. 7. Comparison chart 3 of segmentation effect. (a) Level set algorithm; (b) PixelNet; (c) original U-Net; (d) improved network
    MethodNumber ofsamplesMeanRIOUMeanRACC
    Level set method34700.85620.8775
    PixelNet34700.91870.9405
    Original U-Net34700.92220.9472
    Improved U-Net34700.94020.9630
    Table 1. Objective indexes of testing results
    MethodLevelsetmethodPixelNetOriginalU-NetImprovedU-Net
    Timeconsumption /ms438315276288
    Table 2. Comparison of average time consumption
    Fang Zhang, Yue Wu, Zhitao Xiao, Lei Geng, Jun Wu, Yanbei Liu, Wen Wang. Nanoparticle Segmentation Based on U-Net Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2019, 56(6): 061005
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