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. © The Author 2011. Published by Oxford University Press. All rights reserved.
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CITATION STYLE
Chen, L., Chan, T. H., Choyke, P. L., Hillman, E. M. C., Chi, C. Y., Bhujwalla, Z. M., … Wang, Y. (2011). CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues. Bioinformatics, 27(18), 2607–2609. https://doi.org/10.1093/bioinformatics/btr436
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