Watershed is a widespread technique for image segmentation. Many researchers apply the
method implemented in open source libraries without a deep understanding of its …

Watershed is a widely used image segmentation algorithm. Most researchers understand
just an idea of this method: a grayscale image is considered as topographic relief, which is …

Stressed cells shut down translation, release mRNA molecules from polysomes, and form
stress granules (SGs) via a network of interactions that involve G3BP. Here we focus on the …

The watershed transform has interesting properties that make it useful for many different
image segmentation applications: it is simple and intuitive, can be parallelized, and always …

The image foresting transform (IFT) is a graph-based approach to the design of image
processing operators based on connectivity. It naturally leads to correct and efficient …

We present a supervised classification method which represents each class by one or more
optimum‐path trees rooted at some key samples, called prototypes. The training samples …

We study the watersheds in edge-weighted graphs. We define the watershed cuts following
the intuitive idea of drops of water flowing on a topographic surface. We first establish the …

Automatic contouring for breast tumors using medical ultrasound (US) imaging may assist
physicians without relevant experience, in making correct diagnoses. This study integrates …

We propose an approach for data clustering based on optimum‐path forest. The samples
are taken as nodes of a graph, whose arcs are defined by an adjacency relation. The nodes …

Superpixel segmentation has emerged as an important research problem in the areas of
image processing and computer vision. In this paper, we propose a framework, namely …