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Pyramid Histograms of Motion Context with Application to Angiogram Video Classification

机译:运动上下文的金字塔直方图及其在血管造影视频分类中的应用

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Due to poor image quality as well as the difficulty of modeling the non-rigid heart motion, motion information has rarely been used in the past for angiogram analysis. In this paper we propose a new motion feature for the purpose of classifying angiogram videos according to their viewpoints. Specifically, local motion content of the video around the anatomical structures cardiac vessels is represented using the so-called "motion context", a motion histogram representation in polar coordinates within a local patch. The global motion layout is captured as pyramid histograms of the motion context (PHMC) in a manner similar to that proposed by the Spatial Pyramid Kernel [1]. The PHMC is a robust representation of the motion features in a video sequence. Through experiments on a large database of angiograms obtained from both diseased and control subjects, we show that our technique consistently outperforms state-of-the-art methods in the angiogram classification test.
机译:由于不良的图像质量以及对非刚性心脏运动进行建模的困难,过去很少将运动信息用于血管造影分析。在本文中,我们提出了一种新的运动功能,目的是根据他们的观点对血管造影视频进行分类。具体地,使用所谓的“运动上下文”来表示视频在解剖结构周围的血管周围的局部运动内容,即在局部补丁内的极坐标中的运动直方图表示。以类似于空间金字塔内核[1]提出的方式,将全局运动布局捕获为运动上下文(PHMC)的金字塔直方图。 PHMC是视频序列中运动特征的可靠表示。通过对从患病和对照受试者获得的大型血管造影照片数据库进行的实验,我们表明,我们的技术在血管造影分类测试中始终优于最新技术。

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