内镜下冠状动脉旁路移植术中靶血管的识别

Yifeng Sun, Lixu Gu, Junfeng Cai
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引用次数: 0

摘要

微创直接冠状动脉旁路移植术(MIDCAB)与传统的开放手术相比具有潜在的优势,但一个主要的限制是内窥镜视野狭窄,难以从内窥镜视野中发现狭窄。在本文中,我们提出了一种框架来对齐内窥镜视图和由血管造影重建的3d血管模型。首先利用电磁传感器将内镜视频帧与3d血管模型进行配准,然后利用HSV (hue, saturation, value)变换和hessian变换对内镜视频帧中的血管进行分割,最后利用相干点漂移(Coherent Points Drifting)对血管模型进行细化配准。我们已经在一个静态模拟心脏模型和一个真实病人的内窥镜视频上验证了所提出的方法。采用均方根误差(RMSE)对我们的方法进行评价,模型的配准误差为1.1±0.2mm,真实患者的配准误差为3.1mm。
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Target vessel identification in endoscopic coronary artery bypass grafting
Minimal invasive direct coronary artery bypass grafting (MIDCAB) procedures are potentially advantageous over conventional open surgery, while one major limitation is the narrow view of the endoscope and the difficulty in detecting stenosis from the endoscopic view. In this paper, we propose a frame to align the endoscope view and the 3D-vessel model reconstructed from angiography. We register the endoscopic video frame with the 3D-vessel model by electro-magnetic sensor, and then we segment the vessel in the endoscopic video frame with HSV (hue, saturation, value) and hessian transformation, and refined the registration with the vessel model by Coherent Points Drifting. We have validated the proposed method on a static phantom heart model and a real patient's endoscope video. RMSE (root mean-square error) was employed to evaluate our method and the registration error for the phantom model were 1.1+-0.2mm, for the real patient was 3.1mm.
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