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Chinese Optics, Volume. 17, Issue 4, 971(2024)

Coronary artery angiography image vessel segmentation method based on feature pyramid network

Hao-hu GUO1,2, Ruo-qian GAO2、*, Ming-feng GE2, Wen-fei DONG1,2, Yan LIU1,2, and Xu-feng ZHAO1,2
Author Affiliations
  • 1School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun 130022, China
  • 2Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou 215163, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (11)
    Equations (12)
    References (36)
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    Figures & Tables(11)
    Network structure of the proposed model

    Fig. 1. Network structure of the proposed model

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    ConvNeXt block

    Fig. 2. ConvNeXt block

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    Modified ConvNeXt block

    Fig. 3. Modified ConvNeXt block

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    Feature Pyramid Network

    Fig. 4. Feature Pyramid Network

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    Pyramid Feature Concatenation(PFC)

    Fig. 5. Pyramid Feature Concatenation(PFC)

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    SE attention mechanism

    Fig. 6. SE attention mechanism

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    Group Attention block

    Fig. 7. Group Attention block

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    Dice curves of different algorithms on the testing set

    Fig. 8. Dice curves of different algorithms on the testing set

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    Comparison of segmentation effects with different algorithm

    Fig. 9. Comparison of segmentation effects with different algorithm

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    • Table 1. Each module’s impact on performance

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      Table 1. Each module’s impact on performance

      网络JaccardDice
      BaseNet0.6476±0.00980.7861±0.0073
      BaseNet+Conv.7×70.6606±0.01190.7956±0.0086
      BaseNet+ConvNeXt block0.7104±0.00650.8307±0.0044
      BaseNet+修改后的 ConvNeXt block0.7234±0.00440.8395±0.0030
      BaseNet+PFC0.7036±0.00880.8260±0.0061
      BaseNet+PFC+SE0.7104±0.00430.8260±0.0061
      BaseNet+PFC+SE+加权Loss0.7364±0.00620.8482±0.0041
      BaseNet+GA0.7044±0.00280.8266±0.0019
      BaseNet+Conv.7×7 +PFC+SE +修改后的ConvNeXt block+GA+加权Loss0.7926±0.00580.8843±0.0036

    • Table 2. Test results for different algorithms

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      Table 2. Test results for different algorithms

      网络JaccardDiceAUCAccuracyPrecisionSensitivitySpecificity
      U-Net0.71160.83150.97330.97060.87690.79080.9888
      ResUNeXt0.68490.81300.87410.96830.88470.75260.9901
      TransUnet0.74210.85190.98840.97480.86280.84160.9873
      MultiResUnet0.76640.86770.98420.97610.87750.85830.9879
      Ours0.79260.88430.99130.97830.90080.85970.9904
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    Hao-hu GUO, Ruo-qian GAO, Ming-feng GE, Wen-fei DONG, Yan LIU, Xu-feng ZHAO. Coronary artery angiography image vessel segmentation method based on feature pyramid network[J]. Chinese Optics, 2024, 17(4): 971

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    Paper Information

    Received: Oct. 21, 2023

    Accepted: --

    Published Online: Aug. 9, 2024

    The Author Email:

    DOI:10.37188/CO.2023-0186

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