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利用光学成像对心肌内兴奋中心进行三维定位的方法

Method for the three-dimensional localization of intramyocardial excitation centers using optical imaging.

作者信息

Khait Vadim D, Bernus Olivier, Mironov Sergey F, Pertsov Arkady M

机构信息

State University of New York, Upstate Medical University, Department of Pharmacology, Syracuse, New York 13210, USA.

出版信息

J Biomed Opt. 2006 May-Jun;11(3):34007. doi: 10.1117/1.2204030.

Abstract

This study explores the possibility of localizing the excitation centers of electrical waves inside the heart wall using voltage-sensitive dyes (fluorescent or absorptive). In the present study, we propose a method for the 3-D localization of excitation centers from pairs of 2-D images obtained in two modes of observation: reflection and transillumination. Such images can be obtained using high-speed charge-coupled device (CCD) cameras and photodiode arrays with time resolution up to 0.5 ms. To test the method, we simulate optical signals produced by point sources and propagating ellipsoidal waves in 1-cm-thick slabs of myocardial tissue. Solutions of the optical diffusion equation are constructed by employing the method of images with Robin boundary conditions. The coordinates of point sources as well as of the centers of expanding waves can be accurately determined using the proposed algorithm. The method can be extended to depth estimations of the outer boundaries of the expanding wave. The depth estimates are based on ratios of spatially integrated images. The method shows high tolerance to noise and can give accurate results even at relatively low signal-to-noise ratios. In conclusion, we propose a novel and efficient algorithm for the localization of excitation centers in 3-D cardiac tissue.

摘要

本研究探讨了使用电压敏感染料(荧光或吸收性)定位心壁内电波激发中心的可能性。在本研究中,我们提出了一种从两种观察模式(反射和透照)获得的二维图像对进行激发中心三维定位的方法。此类图像可使用高速电荷耦合器件(CCD)相机和时间分辨率高达0.5毫秒的光电二极管阵列获取。为了测试该方法,我们在1厘米厚的心肌组织切片中模拟了点源产生的光信号和传播的椭球波。通过采用具有罗宾边界条件的镜像法构建光扩散方程的解。使用所提出的算法可以精确确定点源以及扩展波中心的坐标。该方法可扩展到对扩展波外边界的深度估计。深度估计基于空间积分图像的比率。该方法对噪声具有高耐受性,即使在相对较低的信噪比下也能给出准确结果。总之,我们提出了一种用于三维心脏组织中激发中心定位的新颖且高效的算法。

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