Automatic diagnosing of infant hip based on Graf criteria

Xiang Yu, Dongyun Lin, Weiyao Lan, Bingan Zhong, Ping Lv
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引用次数: 1

Abstract

In this paper, we proposed an automatic diagnosis method in detection of infants hips, and experimental results on real ultrasonic images have shown its fastness and capability in the eld. Four procedures, pre-processing of raw images, segmenting, feature extracting and diagnosing, are included in proposed method. Pre-processing mainly focus on obtaining interested region from raw images. Segmenting, followed by features extracting from segmented images, proceeded at once after pre-processing. The algorithm of segmentation we used here is region-scalable tting energy model. Finally, we obtain two most important reference indexes of Graf criteria, angles α and β, by tting lines with least squares method applied. Accordingly, hips are classi ed into one of four types, including maturity, dysplasia, severe dysplasia and dislocation, according to aforementioned indexes. Accuracy on practical images reaches 80.4% with 93 images tested.
基于Graf标准的婴儿髋关节自动诊断
本文提出了一种婴儿髋关节的自动诊断方法,并在真实超声图像上进行了实验,结果表明了该方法的快速性和实时性。该方法包括原始图像的预处理、分割、特征提取和诊断四个步骤。预处理主要集中在从原始图像中获取感兴趣的区域。预处理后立即进行分割,然后从分割后的图像中提取特征。这里我们使用的分割算法是区域可伸缩的分割能量模型。最后,利用最小二乘法求出Graf判据的两个最重要的参考指标:角α和角β。因此,根据上述指标,将髋关节分为成熟型、发育不良型、严重发育不良型和脱位型四种类型之一。测试了93幅实际图像,准确率达到80.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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