| Citation: | LIANG L M，YANG Y，ZHU C K，et al. Fusion of Mobile Vit and inverted gated codec retinal vessel segmentation algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics，2025，51（3）：712-723 （in Chinese） doi: 10.13700/j.bh.1001-5965.2023.0088
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An algorithm based on Mobile Vit and inverted gated codec is proposed for retinal vessel segmentation (FMVG-Net), aiming to tackle issues such background noise interference, boundary texture blurring, and challenging extraction of microvascular areas. First, we improve the Mobile Vit module, and realize the double joint feature extraction cleverly in the coding part. Subsequently, we use the multispectral attention module. The module reduces the missing image feature information from the frequency domain dimension, so as to accurately segment the foreground pixel of the vessel. Next, we propose a feature adaptive fusion module to establish the context dependence of vascular texture and improve the sensitivity of vascular segmentation. In order to enhance the precision of retinal vascular picture segmentation, lastly, we have implemented an inverted gated codec module and optimized the codec structure to further collect deep and spatial semantic information. Experiments are performed on the DRIVE, STARE, and CHASE_DB1 datasets,whereby the obtained specificity are
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