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首页> 外文期刊>Journal of Imaging Science and Technology >Research on Spinal Canal Generation Method based on Vertebral Foramina Inpainting of Spinal CT Images by using BEGAN
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Research on Spinal Canal Generation Method based on Vertebral Foramina Inpainting of Spinal CT Images by using BEGAN

机译：基于椎体围盲盲盲虫染色脊髓型CT图像的脊柱管生成方法研究

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摘要

Spinal surgery is of high risk due to the possibility of neurologic damage, which may cause life-threatening sequelae. Although the emerging robotic-assisted spinal surgery provides better accuracy compared with traditional surgery, the construction of boundary constraints around the spinal canal for safety in surgery is still required. The establishment of a three-dimensional (3D) model of the spinal canal during preoperative preparation can facilitate the generation of surgical boundary constraints. This article presents a novel framework for spinal canal generation based on spinal CT image inpainting by using the boundary equilibrium generative adversarial network (BEGAN). First, U-net is used to simplify the image features and then ResNet50 is applied to classify the vertebral foramen features and mark the area to be restored. Finally, BEGAN generates the target features to complete the vertebral foramina inpainting for the generation of the spinal canal. The experimental results show that the average accuracies (Mean Intersection over Union) of the vertebral foramina and spine inpainting are 0.9396 and 0.9332, respectively, and the accuracy of image inpainting decreases with increase in the inpainting area. The proposed method can accurately generate the vertebral contours and complete the 3D reconstruction of the spinal canal. (C) 2020 Society for Imaging Science and Technology.
机译：由于神经系统损伤的可能性，脊柱手术具有很高的风险，这可能导致危及生命的后遗症。虽然新兴的机器人辅助脊柱手术与传统手术相比提供了更好的准确性，但仍然需要在手术中围绕脊柱管道的边界限制构建。在术前制剂期间建立脊柱管的三维（3D）模型可以促进外科界限约束的产生。本文提出了一种基于边界平衡生成对抗网络（开始）的脊柱CT图像染色的脊柱管道一代新颖框架。首先，U-Net用于简化图像特征，然后应用Reset50来对椎骨雕刻特征进行分类并标记要恢复的区域。最后，开始产生目标特征，以完成椎管围绕脊管管的产生。实验结果表明，椎体围爪和脊柱染色的平均准确性（均匀联盟）分别为0.9396和0.9332，并且图像染色的准确性随着染色区域的增加而降低。所提出的方法可以准确地产生椎体轮廓并完成椎管的三维重建。 （c）2020年影像科技协会。

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  • 来源
    《Journal of Imaging Science and Technology》 |2020年第3期|30505.1-30505.14|共14页
  • 作者

    Ding Li; Sun Yu; Li Shibo; Hu Ying; Tian Wei;

  • 作者单位

    Chinese Acad Sci Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Guangdong Hong Kong Macao Joint Lab Human Machine Shenzhen Peoples R China;

    Chinese Acad Sci Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China;

    Chinese Acad Sci Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Guangdong Hong Kong Macao Joint Lab Human Machine Shenzhen Peoples R China|Shenzhen Inst Artificial Intelligence & Robot Soc SIAT Branch Shenzhen Peoples R China;

    Chinese Acad Sci Shenzhen Inst Adv Technol CAS Key Lab Human Machine Intelligence Synergy Sy Shenzhen 518055 Peoples R China|Guangdong Hong Kong Macao Joint Lab Human Machine Shenzhen Peoples R China|Shenzhen Inst Artificial Intelligence & Robot Soc SIAT Branch Shenzhen Peoples R China;

    Beijing Jishuitan Hosp Dept Spine Surg Beijing 100035 Peoples R China;

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