磁共振电影中运动心脏模式的表征

F. Martínez, A. Manzanera, C. Santa Marta, E. Romero
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引用次数: 4

摘要

心脏磁共振成像(CMRC)最重要的任务之一是识别和描述正常和异常的动态心脏模式,这一任务通常由医生完成。分割和跟踪可以在特定处理过程中支持决策,但它们的性能取决于视频的质量。另一方面,获得的信号受到来自生理运动和设备的噪声的污染,导致心脏边界模糊。本文提出了一种基于局部射流特征分析的连续两帧流心模式自动识别方法。一旦计算出矢量运动场,就会找到空间上相互连接且方差最小的区域作为运动源,并通过不同的统计量客观地估计这些区域的运动模式。通过比较正常和异常患者的这些区域的时间序列,说明了这种方法的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterization of motion cardiac patterns in magnetic resonance cine
One of the most important tasks in Cardiac Magnetic resonance Cine (CMRC) consists in identifying and describing normal and abnormal dynamic heart patterns, a task usually performed by physicians. Segmentation and tracking may support decisions during a particular treatment, but their performance is dependent on the quality of the video. The acquired signal, on the other hand, is contaminated with noise coming from physiological movements and devices, resulting in cardiac blurred boundaries. This paper presents a novel method that automatically identifies flow heart patterns by establishing similarities between two consecutive frames to which a local jet feature analysis has been applied. Once a vector motion field is calculated, spatially connected regions with minimal variance are found as the sources of movement and different statistics objectively estimate movement patterns of these regions. The utility of this method is illustrated by comparing the temporal series of these regions between normal and abnormal patients.
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