增强外科医生的真实感:从延时序列中智能可视化药物到达时间和血流异常,提高脑血管手术的安全性和速度

Andrew Copeland, R. Mangoubi, Mukund Desai, S. Mitter, A. Malek
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引用次数: 0

摘要

提出了一种基于噪声自适应cusum的算法,用于确定血管造影图像在二维时间序列中每个空间位置的对比度到达时间。我们采用了一种新的组智能配准算法来消除在采集过程中患者运动的影响。通过使用配准图像,提出的到达时间提供了准确的结果,而不依赖于对每个位置的时间序列形状的先验知识,甚至不依赖于每个位置的时间序列在平移下具有相同的形状。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing the surgeons reality : Smart visualization of bolus time of arrival and blood flow anomalies from time lapse series for safety and speed of cerebrovascular surgery
A noise adaptive Cusum-based algorithm for determining the arrival times of contrast at each spatial location in a 2D time sequence of angiographic images is presented. We employ a new group-wise registration algorithm to remove the effect of patient motions during the acquisition process. By using the registered image the proposed arrival time provides accurate results without relying on a priori knowledge of the shape of the time series at each location or even on the time series at each location having the same shape under translation.
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