An overview of watershed algorithm implementations in open source libraries
AS Kornilov, IV Safonov - Journal of Imaging, 2018 - mdpi.com
Watershed is a widespread technique for image segmentation. Many researchers apply the
method implemented in open source libraries without a deep understanding of its …
method implemented in open source libraries without a deep understanding of its …
A review of watershed implementations for segmentation of volumetric images
A Kornilov, I Safonov, I Yakimchuk - Journal of Imaging, 2022 - mdpi.com
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 …
just an idea of this method: a grayscale image is considered as topographic relief, which is …
[HTML][HTML] RNA-induced conformational switching and clustering of G3BP drive stress granule assembly by condensation
J Guillén-Boixet, A Kopach, AS Holehouse, S Wittmann… - Cell, 2020 - cell.com
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 …
stress granules (SGs) via a network of interactions that involve G3BP. Here we focus on the …
Improved watershed transform for medical image segmentation using prior information
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 …
image segmentation applications: it is simple and intuitive, can be parallelized, and always …
The image foresting transform: Theory, algorithms, and applications
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 …
processing operators based on connectivity. It naturally leads to correct and efficient …
Supervised pattern classification based on optimum‐path forest
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 …
optimum‐path trees rooted at some key samples, called prototypes. The training samples …
Watershed cuts: Minimum spanning forests and the drop of water principle
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 …
the intuitive idea of drops of water flowing on a topographic surface. We first establish the …
Watershed segmentation for breast tumor in 2-D sonography
YL Huang, DR Chen - Ultrasound in medicine & biology, 2004 - Elsevier
Automatic contouring for breast tumors using medical ultrasound (US) imaging may assist
physicians without relevant experience, in making correct diagnoses. This study integrates …
physicians without relevant experience, in making correct diagnoses. This study integrates …
Data clustering as an optimum‐path forest problem with applications in image analysis
LM Rocha, FAM Cappabianco… - International Journal of …, 2009 - Wiley Online Library
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 …
are taken as nodes of a graph, whose arcs are defined by an adjacency relation. The nodes …
An iterative spanning forest framework for superpixel segmentation
JE Vargas-Muñoz, AS Chowdhury… - … on Image Processing, 2019 - ieeexplore.ieee.org
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 …
image processing and computer vision. In this paper, we propose a framework, namely …