Coronary optical coherence tomography (OCT) is an intravascular, near-infrared light-based
imaging modality capable of reaching axial resolutions of 10–20 µm. This resolution allows …

In this paper we consider a flexible class of models, with elements that are finite mixtures of
multivariate skew-normal independent distributions. A general EM-type algorithm is …

In this paper, a robust sensor fusion method is proposed where the measurement noise is
modeled by a Student-t distribution. The Student-t distribution has a heavy tail compared to …

Finite mixture model based on the Student's-t distribution, which is heavily tailed and more
robust than Gaussian, has recently received great attention for image segmentation. A new …

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general
spatially-or temporally-dependent data, imposing the belief that proximate data are more …

The heterogeneity of Multiple Sclerosis (MS) is a challenge for the disease diagnosis and its
evolution. In order to monitor the treatment and progression of MS, the segmentation and …

In this paper, we combine amplitude and texture statistics of the synthetic aperture radar
images for the purpose of model-based classification. In a finite mixture model, we bring …

Modeling based on finite mixture distributions is a rapidly develo** area with an exploding
range of applications. Finite mixture models are nowadays applied in such diverse areas as …

In this paper, the grayscale image segmentation problem is investigated and a new mixture
model with shifted asymmetric Laplace distribution component is proposed. Instead of the …

Finite mixture models with symmetric distribution have been widely used for many computer
vision and pattern recognition problems. However, in many applications, the distribution of …