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Efficient skeletal bone age estimation method using carpal and radius bone features

机译:利用腕骨和radius骨特征的有效骨骼年龄估算方法

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摘要

This study presents design and implementation of an efficient skeletal bone age assessment (BAA) procedure based on features extracted from two dominant wrist bone structures (radius & carpal bones). System works according to renowned Tanner & Whitehouse (TW2) method, based on carpal and epiphyseal region of interest (ROI). It ensures accurate and robust BAA for both girls and boys (age range, 0-10 y). BAA procedure composes of two components, one dealing with carpal bones [Carpal ROI (CROI) sector] and the other with radius bone segments [Radius ROI (RROI) sector]. Input image is initially cropped to extract desired ROI. Anisotropic diffusion filter is employed to reduce noise before extracting features. This is followed by morphological feature extraction, during which two feature ratios (1 from CROI features and 1 from RROI features) are computed. Feature ratios are used to initially train the system and finally to estimate skeletal bone age. The system was trained with a data set of 120 radiographs (60 males & 60 females) and was tested on a set of 100 radiographs (50 males & 50 females).
机译:这项研究基于从两个主要腕骨结构(radi骨和腕骨)中提取的特征,提出了一种有效的骨骼年龄评估(BAA)程序的设计和实现。系统根据腕骨和epi骨的关注区域(ROI),根据著名的Tanner&Whitehouse(TW2)方法工作。它确保了男孩和女孩(年龄范围为0-10岁)的准确和稳健的BAA。 BAA程序由两个部分组成,一个涉及腕骨[Carpet ROI(CROI)部门],另一个涉及radius骨节段[Radius ROI(RROI)部门]。首先裁剪输入图像以提取所需的ROI。各向异性扩散滤波器用于减少特征提取之前的噪声。接下来是形态特征提取,在此过程中将计算两个特征比率(1个来自CROI特征,1个来自RROI特征)。特征比率用于最初训练系统,最后估计骨骼年龄。该系统使用120幅X射线照片(60例男性和60例女性)的数据集进行了培训,并在100幅X射线照片(50例男性和50例女性)上进行了测试。

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