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VALIDATION OF A COMPUTER-AIDED DIAGNOSIS SYSTEM FOR THE AUTOMATIC IDENTIFICATION OF CAROTID ATHEROSCLEROSIS

机译:用于自动识别颈动脉粥样硬化的计算机辅助诊断系统的验证

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Carotid atherosclerosis represents one of the most important causes of brain stroke. The degree of carotid stenosis is, up to now, considered one of the most important features for determining the risk of brain stroke. Ultrasound (US) is a non-invasive, relatively inexpensive, portable technique, which has an excellent temporal resolution. Computer-aided diagnosis (CAD) has become one of the major research fields in medical and diagnostic imaging. We studied US images of 44 patients, 22 patients with and 22 without carotid artery stenosis, by using US examination and applying a CAD system, an automatic prototype software to detect carotid plaques. We obtained 287 regions: 60 were classified as plaques, with an average signal echogenicity of 244.1 +/- 20.0 and 227 were classified as non-plaques, with an average signal echogenicity of 193.8 +/- 38.6 compared with the opinion of an expert neurologist (golden test). The receiver operating characteristic (ROC) analysis revealed a highly significant area under the ROC curve difference from 0.5 (null hypothesis) in the discrimination between plaques and non-plaques; the diagnostic accuracy was 89% (95% CI: 0.85-0.92), with an appropriate cut-off value of 236.8, sensitivity was 83% and specificity reached a value of 85%. The experimental results showed that the proposed method is feasible and has a good agreement with the expert neurologist. Without the need of any user-interaction, this method generates a detection out-put that may be useful in second opinion. (E-mail: lillabonanno@gmail.com) (C) 2015 World Federation for Ultrasound in Medicine & Biology.
机译:颈动脉粥样硬化代表脑中风的最重要原因之一。迄今为止,颈动脉狭窄的程度被认为是确定脑中风风险的最重要特征之一。超声(US)是一种非侵入性,相对廉价的便携式技术,具有出色的时间分辨率。计算机辅助诊断(CAD)已成为医学和诊断成像的主要研究领域之一。我们通过使用US检查并应用CAD系统(一种用于检测颈动脉斑块的自动原型软件)研究了44例患者,22例有颈动脉狭窄和22例无颈动脉狭窄的美国图像。我们获得了287个区域:60个被分类为斑块,平均信号回声为244.1 +/- 20.0,而227个被分类为非斑块,平均信号回声为193.8 +/- 38.6,与专家神经科医生的意见相比(黄金测试)。接收器工作特性(ROC)分析显示,在ROC曲线差异(从零假设出发)下,在斑块和非斑块之间的区分具有很高的显着性。诊断准确性为89%(95%CI:0.85-0.92),适当的临界值为236.8,敏感性为83%,特异性达到85%。实验结果表明,该方法是可行的,与专家神经科医师具有良好的一致性。不需要任何用户交互,此方法将生成检测输出,该输出可能会在第二方面有用。 (电子邮件:lillabonanno@gmail.com)(C)2015年世界医学与生物学超声联合会。

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