Since the realization that diffusion MRI can probe the microstructural organization and
orientation of biological tissue in vivo and non‐invasively, a multitude of diffusion imaging …

This letter describes algorithms for nonnegative matrix factorization (NMF) with the β-
divergence (β-NMF). The β-divergence is a family of cost functions parameterized by a …

The only single-source——now completely updated and revised——to offer a unified
treatment of the theory, methodology, and applications of the EM algorithm Complete with …

Fully updated throughout, with several new chapters, this second edition of Introduction to
Inverse Problems in Imaging guides advanced undergraduate and graduate students in …

Nonnegative matrix factorization (NMF) has become a widely used tool for the analysis of
high-dimensional data as it automatically extracts sparse and meaningful features from a set …

Spherical deconvolution methods have been applied to diffusion MRI to improve diffusion
tensor tractography results in brain regions with multiple fibre crossing. Recent …

We propose a class of multiplicative algorithms for Nonnegative Matrix Factorization (NMF)
which are robust with respect to noise and outliers. To achieve this, we formulate a new …

Identifying the underlying structure of a data set and extracting meaningful information is a
key problem in data analysis. Simple and powerful methods to achieve this goal are linear …

Nonnegative matrix factorization (NMF) is a data analysis technique used in a great variety
of applications such as text mining, image processing, hyperspectral data analysis …

Improved axial spatial resolution in positron emission tomography (PET) scanners will lead
to reduced sensitivity unless the axial acceptance angle for the coincidences is kept …