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English(EN) Polygon-mamba: Retinal vessel segmentation using polygon scanning mamba and space-frequency collaborative attention

Polygon-mamba网络改进视网膜血管分割

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种名为Polygon-mamba的新型混合CNN-Mamba网络，用于分割视网膜小血管，这项任务对于诊断眼部疾病至关重要。该模型采用多边形扫描视觉状态空间模型（PS-VSS）来更好地保持小血管的连通性，克服了传统水平-垂直扫描的局限性。此外，还使用了时频协同注意力机制（SFCAM），通过整合空间和频域信息来增强特征提取。在三个公开数据集上进行测试，Polygon-mamba取得了具有竞争力的性能，F1分数约为0.828，AUC值接近0.98。 AI

影响 引入了一种新的医学图像分割模型架构，有望提高眼部疾病的诊断准确性。

排序理由 发表了一篇关于新型计算机视觉模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Polygon-mamba网络改进视网膜血管分割

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发表了一篇关于新型计算机视觉模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Juan Zhou ·

    Polygon-mamba：使用多边形扫描mamba和时频协同注意力进行视网膜血管分割

    Retinal vessel segmentation is crucial for diagnosis and assessment of ocular diseases. Notably, segmentation of small retinal vessels has been consistently recognized as a challenging and complex task. To tackle this challenge, we design a hybrid CNN-Mamba fusion network that in…

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