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Enhancing the convex analysis of mixtures technique for estimating DCE-MRI pharmacokinetic parameters

机译:增强混合物技术估算估算DCE-MRI药代动力学参数的凸分析

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Dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) is a useful noninvasive tool for monitoring tumor angiogenesis and assessing therapeutic response. One major problem that prevents an accurate estimation of pharmacokinetic parameters is partial-volume effect (PVE). A multi-tissue compartmental modeling (CM) technique supported by convex analysis of mixtures (CAM) is used to overcome the PVE by clustering pixels and constructing a simplex whose vertices are of a single compartment type. CAM uses the identified pure-volume pixels to estimate the kinetics of the tissues under investigation. This paper reports an enhanced version of CAM-CM to identify pure-volume pixels more accurately. This includes the consideration of the neighborhood effect on each pixel and the use of a barycentric coordinate system to identify more pure-volume pixels and to test those identified by CAM. The enhanced CAM achieved root mean square error (RMSE) of 0.00348 ± 0.000019, lower than the RMSE of 0.05409 ± 0.00496 achieved by CAM.
机译:动态对比增强磁共振成像(DCE-MRI)是一种用于监测肿瘤血管生成和评估治疗反应的有用的非侵入性工具。防止准确估计药代动力学参数的一个主要问题是部分体积效应(PVE)。通过聚类像素(CAM)凸分析支持的多组织隔间建模(CM)技术通过聚类像素来克服PVE,并构造其顶点的单个隔室类型的单独。 CAM使用所识别的纯体像素来估计正在调查的组织的动力学。本文报告了CAM-CM的增强版本,以更准确地识别纯体像素。这包括考虑对每个像素的邻域效应以及使用重心坐标系来识别更多纯体积像素并测试由凸轮识别的那些。增强型凸轮实现了0.00348±0.000019的根均方误差(RMSE),低于CAM实现的0.05409±0.00496的RMSE。

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