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Semi-Automatic Assessment of Pediatric Hydronephrosis Severity in 3D Ultrasound

机译:三维超声中儿科肾内肾小序严重程度的半自动评估

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Hydronephrosis is the most common abnormal finding in pediatric urology. Thanks to its non-ionizing nature, ultrasound (US) imaging is the preferred diagnostic modality for the evaluation of the kidney and the urinary track. However, due to the lack of correlation of US with renal function, further invasive and/or ionizing studies might be required (e.g., diuretic renograms). This paper presents a computer-aided diagnosis (CAD) tool for the accurate and objective assessment of pediatric hydronephrosis based on morphological analysis of kidney from 3DUS scans. The integration of specific segmentation tools in the system, allows to delineate the relevant renal structures from 3DUS scans of the patients with minimal user interaction, and the automatic computation of 90 anatomical features. Using the washout half time (T_(1/2) as indicative of renal obstruction, an optimal subset of predictive features is selected to differentiate, with maximum sensitivity, those severe cases where further attention is required (e.g., in the form of diuretic renograms), from the non-critical ones. The performance of this new 3DUS-based CAD system is studied for two clinically relevant T_(1/2) thresholds, 20 and 30 min. Using a dataset of 20 hydronephrotic cases, pilot experiments show how the system outperforms previous 2D implementations by successfully identifying all the critical cases (100% of sensitivity), and detecting up to 100% (T_(1/2) = 20 min) and 67% (T_(1/2 )= 30 min) of non-critical ones for T_(1/2) thresholds of 20 and 30 min, respectively.
机译:肾积水是小儿泌尿外科最常见的异常发现。由于其非离子性质,超声(US)成像是用于肾的评价和泌尿轨道的优选的诊断方式。然而,由于缺乏肾功能,进一步的侵入和/或电离研究美国的相关性可能需要(例如,利尿renograms)。本文提出了一种基于从三维超声扫描肾脏形态分析小儿肾积水的准确和客观的评估计算机辅助诊断(CAD)工具。在系统的具体分割工具的集成,允许划定有关肾结构从三维超声扫描的患者最少的用户交互,和90个的解剖特征的自动计算。使用冲洗半时间(T_(1/2)作为指示肾阻塞的,预测特征的最佳子集被选择来区分,具有最大的灵敏度,那些其中需要进一步注意(例如,在利尿renograms的形式严重的情况下),来自。这个新的基于三维超声-CAD系统的性能进行了研究两个临床相关T_(1/2)的阈值,20和30分钟。使用20积水情况的数据集的非关键的,导频实验表明如何系统,远远超过前2D实现通过成功地识别所有关键例(灵敏度的100%),并检测最高达100%(T_(1/2)= 20分钟)和67%(T_(1/2)= 30分钟)的非关键药粥T_(1/2)的20和30分钟,分别阈值。

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