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Computer-aided recognition of a four-chamber image plane in three-dimensional echocardiographic images of children

机译:儿童三维超声心动图图像中四腔图像平面的计算机辅助识别

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摘要

Automated detection of the clinically relevant image planes in a three-dimensional echocardiographic (3-DE) data set has potential applications for diagnosis of pediatric congenital heart disease. We propose a method based on template matching to automatically detect the four-chamber image plane (4CIP) in a 3-DE data set. First, a normal four-chamber image is chosen as the template. Second, to find the 4CIP in a 3-D volume, a series of cross sections are extracted from this volume. Then, a coarse-to-fine retrieval is applied to the stack of slices and the image most similar to the template is proposed as the 4CIP of this volume. We tested the method on 28 data sets of normal children and 22 data sets of children suffering from congenital heart disease, and the error rates are 7 and 9%, respectively. As will be shown, the autodetection algorithm can be straightforwardly implemented, has low computational complexity, and is robust to noise.
机译:三维超声心动图(3-DE)数据集中临床相关图像平面的自动检测在诊断小儿先天性心脏病方面具有潜在的应用。我们提出一种基于模板匹配的方法,以自动检测3-DE数据集中的四腔图像平面(4CIP)。首先,选择正常的四腔图像作为模板。其次,要在3D体积中找到4CIP,请从该体积中提取一系列横截面。然后,从粗到细检索应用于切片堆栈,并提出最类似于模板的图像作为该体积的4CIP。我们在28名正常儿童和22名先天性心脏病儿童的数据集上测试了该方法,错误率分别为7%和9%。如将显示的那样,自动检测算法可以被直接实现,具有低的计算复杂度并且对噪声是鲁棒的。

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