title: Modeling and reconstruction of mixed functional and molecular patterns.
abstract: Functional medical imaging promises powerful tools for the visualization and elucidation of important disease-causing biological processes in living tissue. Recent research aims to dissect the distribution or expression of multiple biomarkers associated with disease progression or response, where the signals often represent a composite of more than one distinct source independent of spatial resolution. Formulating the task as a blind source separation or composite signal factorization problem, we report here a statistically principled method for modeling and reconstruction of mixed functional or molecular patterns. The computational algorithm is based on a latent variable model whose parameters are estimated using clustered component analysis. We demonstrate the principle and performance of the approaches on the breast cancer data sets acquired by dynamic contrast-enhanced magnetic resonance imaging.
authors.affiliation: Department of Electrical and Computer Engineering, Computational Bioinformatics and Bioimaging Laboratory, Virginia Polytechnic Institute and State University, 4300 Wilson Boulevard, Suite 750, Arlington, VA 22203, USA.
authors.forename: Yue
authors.initials: Y
authors.lastname: Wang
authors.forename: Jianhua
authors.initials: J
authors.lastname: Xuan
authors.forename: Rujirutana
authors.initials: R
authors.lastname: Srikanchana
authors.forename: Peter L
authors.initials: PL
authors.lastname: Choyke