[POSTER]基于多剪影图像的弹性体内窥镜图像增强变形估计

Akira Saito, M. Nakao, Yuuki Uranishi, T. Matsuda
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引用次数: 20

摘要

本研究提出了一种利用从多个内窥镜图像中获得的轮廓来估计弹性变形的方法。我们的方法可以利用术前CT数据重建的体积网格模型来估计术中器官的变形。我们利用弹性体的轮廓信息来估计局部位移,而不是建立弹性体的形状模型。模型形状被更新以满足轮廓约束,同时尽可能地保留形状。实验结果表明,该方法可以估计变形,均方根误差(RMS)为5.0±10 mm。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[POSTER] Deformation Estimation of Elastic Bodies Using Multiple Silhouette Images for Endoscopic Image Augmentation
This study proposes a method to estimate elastic deformation using silhouettes obtained from multiple endoscopic images. Our method can estimate the intraoperative deformation of organs using a volumetric mesh model reconstructed from preoperative CT data. We use this elastic body silhouette information of elastic bodies not to model the shape but to estimate the local displacements. The model shape is updated to satisfy the silhouette constraint while preserving the shape as much as possible. The result of the experiments showed that the proposed methods could estimate the deformation with root mean square (RMS) errors of 5.0–10 mm.
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