In order to efficiently extract the focused regions from the source images and improve the quality of the fused image, this paper presents a novel image fusion scheme with non-negative matrix factorization (NMF). The source images are fused by NMF to construct temporary fused image, whose region homogeneityis used to split the source images into regions.The focused regions are detected and inte...

A method for detecting the position of cells from multi-cellular calcium imaging data using non-negative matrix factorization is presented. Contamination of the background in the cell signals is effectively avoided by treating it as a distinct component with a constraint. The validity of the method is tested upon simulated and real calcium imaging data. Keywords— Calcium imaging, cell sorting, ...

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...

We present a general method for including prior knowledge in a nonnegative matrix factorization (NMF), based on Gaussian process priors. We assume that the nonnegative factors in the NMF are linked by a strictly increasing function to an underlying Gaussian process specified by its covariance function. This allows us to find NMF decompositions that agree with our prior knowledge of the distribu...

Identifying overlapping communities in networks is a challenging task. In this work we present a novel approach to community detection that utilizes the Bayesian non-negative matrix factorization (NMF) model to extract overlapping modules from a network. The scheme has the advantage of computational efficiency, soft community membership and an intuitive foundation. We present the performance of...