• Laser & Optoelectronics Progress
  • Vol. 59, Issue 2, 0210010 (2022)
Sanli Yi1、2, Tianwei Wang1、2, Xuelian Yang1、2, Furong She1、2, and Jianfeng He1、2、*
Author Affiliations
  • 1School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming , Yunnan 650500, China
  • 2Key Laboratory of Computer Technology Application of Yunnan Province, Kunming , Yunnan 650500, China
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    DOI: 10.3788/LOP202259.0210010 Cite this Article Set citation alerts
    Sanli Yi, Tianwei Wang, Xuelian Yang, Furong She, Jianfeng He. Lung Field Segmentation Algorithm Based on Improved U-Net[J]. Laser & Optoelectronics Progress, 2022, 59(2): 0210010 Copy Citation Text show less
    Structure of the inception module
    Fig. 1. Structure of the inception module
    Structure of the residual module
    Fig. 2. Structure of the residual module
    Structure of the skip connection
    Fig. 3. Structure of the skip connection
    Structure of the scSE module
    Fig. 4. Structure of the scSE module
    Sructure of the improved U-Net
    Fig. 5. Sructure of the improved U-Net
    Flow chart of our algorithm
    Fig. 6. Flow chart of our algorithm
    Segmentation results of different algorithms. (a) Original image; (b) label; (c) ENet; (d) U-Net; (e) our algorithm
    Fig. 7. Segmentation results of different algorithms. (a) Original image; (b) label; (c) ENet; (d) U-Net; (e) our algorithm
    AUC of different algorithms
    Fig. 8. AUC of different algorithms
    AlgorithmAccuracyRecallSpecificityMIoU
    ET-Net98.65--94.20
    ENet98.5796.6799.1896.20
    U-Net98.5996.8199.1896.33
    Ours98.9097.8199.2897.17
    Table 1. Segmentation results of different algorithms
    AlgorithmAccuracyRecallSpecificityMIoU
    ET-Net98.6896.23
    CE-Net2399.0098.00
    Ours99.5298.8699.7498.73
    Table 2. Comparison of segmentation results of different algorithms
    Sanli Yi, Tianwei Wang, Xuelian Yang, Furong She, Jianfeng He. Lung Field Segmentation Algorithm Based on Improved U-Net[J]. Laser & Optoelectronics Progress, 2022, 59(2): 0210010
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