利用二维多普勒超声心动图自动评估主动脉瓣返流

N. Kiruthika, B. Prabhakar, M. Reddy
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引用次数: 12

摘要

本文介绍一种基于二维多普勒超声心动图的无创自动评估主动脉瓣返流严重程度的方法。采用GE超声机配备1.7MHz至15MHz相控阵换能器。连续波(CW)彩色多普勒超声心动图图像的主动脉瓣,前线生命线医院,钦奈,印度。应用图像处理技术提取多普勒指数。提出的算法自动检测频谱多普勒超声跟踪的峰值速度包络,用于计算单个屏幕帧内可用的压力半衰期(PHT)。从最大速度包络线中自动提取的测量值与人工获得的测量值进行了比较,其中用于AR严重程度评估的PHT显示出很强的正相关性(r=0.950313)。目前的工作提供了一种新的自动化工具,用于从2D多普勒图像中提取临床参数并评估AR的严重程度,从而克服了手工技术的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Assessment of Aortic Regurgitation using 2D Doppler Echocardiogram
Based on 2D Doppler echocardiography a non-invasive automated method for assessing the severity of Aortic Regurgitation (AR) is explained in this paper. Using GE ultrasound machine equipped with 1.7MHz to 15MHz phased array transducers. Continuous Wave (CW) color Doppler echocardiographic images of aortic valve were obtained from Frontier Life Line Hospital, Chennai, India. Doppler index is extracted by applying image processing techniques. Proposed algorithm automatically detects Peak velocity envelope of the spectral Doppler ultrasound tracings for calculating Pressure Half Time (PHT) available in a single screen frame. Measurements extracted automatically from the maximal velocity envelope are compared with measurements obtained manually where PHT for severity assessment of AR show strong positive correlation (r=0.950313). Present work provides a novel automated tool for extraction of clinical parameters from 2D Doppler images and assesses the severity of AR thus overcoming the short comings of the manual technique.
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