Modeling and Reconstruction of Mixed Functional and Molecular Patterns

Wang, Yue; Xuan, Jianhua; Srikanchana, Rujirutana; Choyke, Peter L.

doi:https://doi.org/10.1155/IJBI/2006/29707

International Journal of Biomedical Imaging

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Volume 2006 | Article ID 029707 | https://doi.org/10.1155/IJBI/2006/29707

Modeling and Reconstruction of Mixed Functional and Molecular Patterns

Yue Wang,¹Jianhua Xuan,²Rujirutana Srikanchana,³and Peter L. Choyke⁴

Academic Editor: Ming Jiang

Received10 Aug 2005

Accepted23 Oct 2005

Published17 Jan 2006

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.

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Copyright

Copyright © 2006 Yue Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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