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

Li Chen, Tsung Han Chan, Peter L. Choyke, Elizabeth M.C. Hillman, Chong Yung Chi, Zaver M. Bhujwalla, Ge Wang, Sean S. Wang, Zsolt Szabo, Yue Wang

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


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.

Original languageEnglish (US)
Article numberbtr436
Pages (from-to)2607-2609
Number of pages3
Issue number18
StatePublished - Sep 2011
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


Dive into the research topics of 'CAM-CM: A signal deconvolution tool for in vivo dynamic contrast-enhanced imaging of complex tissues'. Together they form a unique fingerprint.

Cite this