Optics and Precision Engineering, Volume. 31, Issue 23, 3482(2023)

Automatic segmentation of choroid by TransGLnet integrating attention mechanism

Wenbo HUANG*... Chaofan QU and Yang YAN |Show fewer author(s)
Author Affiliations
  • School of Computer Science and Technology, Changchun Normal University,Changchun130032, China
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    Figures & Tables(9)
    Overall framework of TransGLnet
    Structure of global attention module
    Process of local attention module
    Schematic of feature fusion process
    Choroidal labeling process
    Visualization of choroid segmentation example results
    Visualization of results of lung segmentation example
    Ablation experiment results
    • Table 1. Comparison of choroid segmentation results among different networks

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      Table 1. Comparison of choroid segmentation results among different networks

      NetDiceAccMIOUF1_scoreHD
      U-Net0.870.970.870.878.34
      AttU-Net0.860.970.860.868.43
      R2U-Net0.880.970.880.887.25
      R2AU-Net0.870.970.880.877.79
      TransUnet0.810.960.830.9010.32
      Swin-Unet0.860.970.860.868.41
      Ours0.910.980.890.916.56
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    Wenbo HUANG, Chaofan QU, Yang YAN. Automatic segmentation of choroid by TransGLnet integrating attention mechanism[J]. Optics and Precision Engineering, 2023, 31(23): 3482

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    Paper Information

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    Received: Jun. 15, 2023

    Accepted: --

    Published Online: Jan. 5, 2024

    The Author Email: HUANG Wenbo (huangwenbo@sina.com)

    DOI:10.37188/OPE.20233123.3482

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