Multiple Nonnegative-matrix Factorization of Dynamic Pet Images
نویسندگان
چکیده
We propose an extension of nonnegative matrix factorization (NMF) to multilayer network model for dynamic myocardial PET image analysis. NMF has been previously applied to the analysis and shown to successfully extract three cardiac components and time-activity curve from the image sequences. Here we apply triple nonnegative-matrix factorization to the dynamic PET images of dog and show details of cardiac components. We think of the multiple nonnegative-matrix factorization as a model that can learn a hierarchical-parts representation.
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