Chinese Journal of Lasers, Volume. 51, Issue 15, 1507208(2024)

Retinal Vessel Segmentation Based on Dynamic Feature Graph Convolutional Network

Linyi Miao and Feng Li*
Author Affiliations
  • School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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    References(36)

    [12] Zhang L, Wu C, Fan X Y et al. Retinal vessel segmentation via self-adaptive compensation network[J]. Acta Optica Sinica, 43, 1418001(2023).

    [14] Liang L M, Yu J, Zhou L S et al. Multiscale dense attention network for retinal vessel segmentation[J]. Laser & Optoelectronics Progress, 60, 0610011(2023).

    [18] Lü J, Liang H C, Wang Z Y. Retinal vascular contour and high uncertainty regional refinement framework based on graph convolution[J]. Journal of Optoelectronics·Laser, 34, 654-662(2023).

    [19] Lü J, Wang Z Y, Liang H C. Boundary attention assisted dynamic graph convolution for retinal vascular segmentation[J]. Opto-Electronic Engineering, 50, 220116(2023).

    [22] Yang J, Yu X Z. Semantic segmentation of high-resolution remote sensing images based on improved FuseNet combined with atrous convolution[J]. Geomatics and Information Science of Wuhan University, 47, 1071-1080(2022).

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    Linyi Miao, Feng Li. Retinal Vessel Segmentation Based on Dynamic Feature Graph Convolutional Network[J]. Chinese Journal of Lasers, 2024, 51(15): 1507208

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    Paper Information

    Category: Optical Diagnostics and Therapy

    Received: Jan. 15, 2024

    Accepted: Mar. 6, 2024

    Published Online: Jul. 16, 2024

    The Author Email: Li Feng (lifenggold@163.com)

    DOI:10.3788/CJL240498

    CSTR:32183.14.CJL240498

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