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Quantification of kidneys from 3D ultrasound in pediatric hydronephrosis

机译:从3D超声对小儿肾积水的肾脏定量

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This paper introduces a complete framework for the quantification of renal structures (parenchyma, and collecting system) in 3D ultrasound (US) images. First, the segmentation of the kidney is performed using Gabor-based appearance models (GAM), a variant of the popular active shape models, properly tailored to the imaging physics of US image data. The framework also includes a new graph-cut based method for the segmentation of the collecting system, including brightness and contrast normalization, and positional prior information. The significant advantage (p = 0.03) of the new method over previous approaches in terms of segmentation accuracy has been successfully verified on clinical 3DUS data from pediatric cases with hydronephrosis. The promising results obtained in the estimation of the volumetric hydronephrosis index demonstrate the potential of our new framework to quantify anatomy in US and asses the severity of hydronephrosis.
机译:本文介绍了用于量化3D超声(US)图像中肾脏结构(实质和收集系统)的完整框架。首先,使用基于Gabor的外观模型(GAM)进行肾脏分割,GAM是流行的主动形状​​模型的一种变体,适合于美国图像数据的成像物理学。该框架还包括一种基于图割的新方法,用于对收集系统进行分割,包括亮度和对比度归一化以及位置先验信息。在分割准确性方面,该新方法相对于先前方法的显着优势(p = 0.03)已在来自肾积水患儿的临床3DUS数据上得到了成功验证。在估计体积性肾积水指数中获得的有希望的结果证明了我们新框架在量化美国解剖结构和评估肾积水严重程度方面的潜力。

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