scholarly journals 3D Markov Random Fields and Region Growing for Interactive Segmentation of MR Data

Author(s):  
Marc Liévin ◽  
Nils Hanssen ◽  
Peter Zerfass ◽  
Erwin Keeve
Author(s):  
S. Zimeras

Segmentation is a powerful procedure that could be used to extract relevant information of the images based on advanced techniques (like active contours, region growing, Markov random fields, and medical atlas analysis). For the procedures, the main task is the contour, or volume or surface representation of specific parts of the organs that could be used for the benefit of the patients under doctor evaluation. So, in real cases, the proposed process must be quick, accurate and easy to implement. The segmentation of the organ is another problem that must be considered. More complicated, more demanding the segmentation process. In our case (bronchus segmentation) a quick, effective and easy to implement procedure is proposed based on the combination of boundary tracking and region growing techniques.


2008 ◽  
Vol 48 ◽  
pp. 1041 ◽  
Author(s):  
Daniel Peter Simpson ◽  
Ian W. Turner ◽  
A. N. Pettitt

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1389
Author(s):  
Julia García Cabello ◽  
Pedro A. Castillo ◽  
Maria-del-Carmen Aguilar-Luzon ◽  
Francisco Chiclana ◽  
Enrique Herrera-Viedma

Standard methodologies for redesigning physical networks rely on Geographic Information Systems (GIS), which strongly depend on local demographic specifications. The absence of a universal definition of demography makes its use for cross-border purposes much more difficult. This paper presents a Decision Making Model (DMM) for redesigning networks that works without geographical constraints. There are multiple advantages of this approach: on one hand, it can be used in any country of the world; on the other hand, the absence of geographical constraints widens the application scope of our approach, meaning that it can be successfully implemented either in physical (ATM networks) or non-physical networks such as in group decision making, social networks, e-commerce, e-governance and all fields in which user groups make decisions collectively. Case studies involving both types of situations are conducted in order to illustrate the methodology. The model has been designed under a data reduction strategy in order to improve application performance.


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