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CAM-CM: a signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues

机译:CAM-CM:用于复杂组织的体内动态对比增强成像的信号去卷积工具

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In vivo dynamic contrast-enhanced imaging tools provide non-invasive methods for analyzing various functional changes associated with disease initiation, progression and responses to therapy. The quantitative application of these tools has been hindered by its inability to accurately resolve and characterize targeted tissues due to spatially mixed tissue heterogeneity. Convex Analysis of Mixtures - Compartment Modeling (CAM-CM) signal deconvolution tool has been developed to automatically identify pure-volume pixels located at the corners of the clustered pixel time series scatter simplex and subsequently estimate tissue-specific pharmacokinetic parameters. CAM-CM can dissect complex tissues into regions with differential tracer kinetics at pixel-wise resolution and provide a systems biology tool for defining imaging signatures predictive of phenotypes.Availability: The MATLAB source code can be downloaded at the authors' website www.cbil.ece.vt.edu/software.htmContact: yuewang@vt.eduSupplementary information: Supplementary data are available at Bioinformatics online.
机译:体内动态对比增强成像工具提供了非侵入性方法来分析与疾病的发生,进展和对治疗的反应相关的各种功能变化。这些工具的定量应用由于空间混合的组织异质性而无法准确解析和表征目标组织而受到阻碍。混合物的凸分析-隔室建模(CAM-CM)信号去卷积工具已经开发出来,可以自动识别位于聚类像素时间序列角上的纯体积像素,从而散射单形并随后估计组织特定的药代动力学参数。 CAM-CM可以按像素分辨率将示踪剂动力学分解为具有不同示踪剂动力学的区域,并提供系统生物学工具来定义可预测表型的成像特征。 ece.vt.edu/software.htm联系人:yuewang@vt.edu补充信息:补充数据可从Bioinformatics在线获得。

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