反褶积
对比度(视觉)
信号(编程语言)
动态对比度
计算机科学
体内
动态成像
人工智能
生物医学工程
计算机视觉
算法
图像处理
生物
放射科
医学
图像(数学)
磁共振成像
数字图像处理
程序设计语言
生物技术
作者
Li Chen,Tsung‐Han Chan,Peter L. Choyke,Elizabeth M. C. Hillman,Chong−Yung Chi,Zaver M. Bhujwalla,Ge Wang,Sean S. Wang,Zsolt Szabó,Yue Wang
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2011-07-23
卷期号:27 (18): 2607-2609
被引量:25
标识
DOI:10.1093/bioinformatics/btr436
摘要
Abstract Summary: 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.htm Contact: yuewang@vt.edu Supplementary information: Supplementary data are available at Bioinformatics online.
科研通智能强力驱动
Strongly Powered by AbleSci AI