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Target vessel identification in endoscopic coronary artery bypass grafting

机译:内镜下冠状动脉搭桥术中的目标血管识别

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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.
机译:微创直接冠状动脉旁路移植术(MIDCAB)程序可能优于传统的开放手术,而一个主要限制是内窥镜的狭窄视野和从内窥镜视野检测狭窄的困难。在本文中,我们提出了一个框架,以使内窥镜视图与从血管造影术重建的3D血管模型对齐。我们通过电磁传感器将内窥镜视频帧与3D血管模型配准,然后通过HSV(色相,饱和度,值)和粗麻布变换在内窥镜视频帧中对血管进行分割,并完善与血管模型的配准通过连贯点漂移。我们已经在静态幻影心脏模型和真实患者的内窥镜视频上验证了该方法。采用RMSE(均方根误差)来评估我们的方法,体模模型的配准误差为1.1±0.2mm,而实际患者为3.1mm。

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