scholarly journals Implementation of graph-based interactive 3D vessel segmentation filter

2010 ◽  
Author(s):  
David Pellow ◽  
Mot Freiman ◽  
Leo Joskowicz

This paper describes an ITK implementation of a 3D vascular segmentation filter using a graph-based energy minimization algorithm. The method first computes the shortest path between two user provided points in the vessel and then performs a graph min-cut based segmentation of the vessel based on the intensity information coupled with the computed path as a spatial constraint. The shortest path computation is adapted from the algorithm in [1] to use a vesselness based weighting function. The min-cut algorithm uses the Boost graph library to calculate the minimal cut. Several examples of applications are provided, along with images of the resulting segmentations.

2021 ◽  
Vol 14 (11) ◽  
pp. 2127-2140
Author(s):  
Mengxuan Zhang ◽  
Lei Li ◽  
Xiaofang Zhou

Shortest path computation is a building block of various network applications. Since real-life networks evolve as time passes, the Dynamic Shortest Path (DSP) problem has drawn lots of attention in recent years. However, as DSP has many factors related to network topology, update patterns, and query characteristics, existing works only test their algorithms on limited situations without sufficient comparisons with other approaches. Thus, it is still hard to choose the most suitable method in practice. To this end, we first identify the determinant dimensions and constraint dimensions of the DSP problem and create a complete problem space to cover all possible situations. Then we evaluate the state-of-the-art DSP methods under the same implementation standard and test them systematically under a set of synthetic dynamic networks. Furthermore, we propose the concept of dynamic degree to classify the dynamic environments and use throughput to evaluate their performance. These results can serve as a guideline to find the best solution for each situation during system implementation and also identify research opportunities. Finally, we validate our findings on real-life dynamic networks.


Author(s):  
Dekonda Sindhuja ◽  
◽  
R Vasavi ◽  
A Kousar Nikhath

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