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3D Optical Flow Estimation in Cardiac CT Images using the Hermite transform

机译:使用Hermite变换在心脏CT图像中进行3D光流估计

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Heart diseases are one of the most important causes of death in the Western world. It is, then, important to implement algorithms to aid the specialist in analyzing the heart motion. We propose a new strategy to estimate the cardiac motion through a 3D optical flow differential technique that uses the Steered Hermite transform (SHT). SHT is a tool that performs a decomposition of the images in a base that model the visual patterns used by the human vision system (HSV) for processing the information. The 3D+t analysis allows to describe most of motions of the heart, for example, the twisting motion that takes place on every beat cycle and to identify abnormalities of the heart walls. Our proposal was tested on two phantoms and on two sequences of cardiac CT images corresponding to two different patients. We evaluate our method using a reconstruction schema, for this, the resulting 3D optical flow was applied over the volume at time t to obtain a estimated volume at time t + 1. We compared our 3D optical flow approach to the classical Horn and Shunk's 3D algorithm for different levels of noise.
机译:心脏病是西方世界最重要的死亡原因之一。因此,重要的是要实施算法来帮助专家分析心脏运动。我们提出了一种新的策略,通过使用Steered Hermite变换(SHT)的3D光流微分技术来估计心脏运动。 SHT是一种在基础上对图像进行分解的工具,该基础可对人类视觉系统(HSV)用于处理信息的视觉模式进行建模。 3D + t分析可以描述心脏的大多数运动,例如,在每个心跳周期中发生的扭曲运动,并可以识别心脏壁的异常情况。我们的建议在两个体模上以及在与两个不同患者相对应的两个心脏CT图像序列上进行了测试。我们使用重构方案评估我们的方法,为此,将所得3D光流应用于时间t的体积,以获得时间t + 1处的估计体积。我们将3D光流方法与经典的Horn和Shunk的3D进行了比较不同噪声水平的算法。

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