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首页> 外文会议>Conference on Physiology and Function: Methods, Systems, and Applications Feb 16-18, 2003 San Diego, California, USA >Left ventricle motion estimation based on signal-dependent time-frequency representation
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Left ventricle motion estimation based on signal-dependent time-frequency representation

机译：基于信号相关时频表示的左心室运动估计

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摘要

In current clinical practice, the noninvasive assessment of left ventricular deformation can be determined using all the principal imaging modalities, including contrast angiography, echocardiography, cine computed tomography, single photon emission tomography and magnetic resonance imaging. However, since the heart undergoes complex motion, proper characterization of its motion still remains an open and challenging research problem. A number of approaches for nonrigid motion analysis have been studied in the literature. Much of the effort has confined to estimate the displacement vector for each image point or optical flow. This is a challenging problem in image analysis because of a wide range of possible motions and the presence of noise in the image sets. In this work, we present an algorithm for computation of optical flow based on a signal-dependent radially Gaussian kernel that adapts over time. The adaptive kernel obtained from the proposed algorithm is used to estimate a 3D-frequency spectrum for a given pixel in a series of images. The orientation of the spectrum in the frequency domain is totally governed by the pixel velocity. In a recent contribution, a linear regression model is used over the spectrum to obtain the velocity components that are proportional to the pixel movement.
机译：在当前的临床实践中，可以使用所有主要的成像方式来确定左心室变形的非侵入性评估，包括造影剂血管造影，超声心动图，电影计算机断层扫描，单光子发射断层扫描和磁共振成像。然而，由于心脏经历复杂的运动，对其运动的正确表征仍然是一个开放且具有挑战性的研究问题。在文献中已经研究了许多用于非刚性运动分析的方法。大部分工作都局限于估算每个像点或光流的位移矢量。这是图像分析中一个具有挑战性的问题，因为可能的运动范围很广，并且图像集中存在噪声。在这项工作中，我们提出了一种基于随时间变化的信号相关径向高斯核的光流计算算法。从提出的算法获得的自适应内核用于估计一系列图像中给定像素的3D频谱。频谱在频域中的方向完全取决于像素速度。在最近的贡献中，在光谱上使用线性回归模型以获得与像素运动成比例的速度分量。

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