This paper surveys the opportunities and challenges in an emerging area of research that
has the potential to significantly ease the incorporation of renewable energy into the grid as …

Markov random field (MRF) is a widely used probabilistic model for expressing interaction of
different events. One of the most successful applications is to solve image labeling problems …

Segmentation of an ultrasound image into functional tissues is of great importance to clinical
diagnosis of breast cancer. However, many studies are found to segment only the mass of …

Intravascular optical coherence tomography (IV-OCT) allows evaluation of atherosclerotic
plaques; however, plaque characterization is performed by visual assessment and requires …

Accurate tissue and structure segmentation of magnetic resonance (MR) brain scans is
critical in several applications. In most approaches this task is handled through two …

Intravascular ultrasound (IVUS) is a catheter-based medical imaging technique that
produces cross-sectional images of blood vessels and is particularly useful for studying …

Spatially varying mixture models are characterized by the dependence of their mixing
proportions on location (contextual mixing proportions) and they have been widely used in …

This paper focuses on an entropy based formalism to speed up the evaluation of the
Structural SIMilarity (SSIM) index in images affected by a global distortion. Looking at …

We present a method for foreground/background video segmentation (change detection) in
real-time that can be used, in applications such as background subtraction or analysis of …

Image segmentation is a very important step in image analysis, and performance evaluation
of segmentation algorithms plays a key role both in develo** efficient algorithms and in …