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Many medical image segmentation techniques have been proposed by lots of authors but they are mainly dedicated to particular solutions. There is no generic method for solving the image segmentation problem. The difficulty comes from that two types of noise are presented in medical images: physical noise due to the acquisition system, for example, Optical, X-rays and MRI, and physiological noise due...
Sensor-network technology is indispensable for constructing ubiquitous network infrastructures. Although information about adjacent relations between sensors is also very important for sensor networks, obtaining this information automatically without manual assistance is extremely difficult. Consequently, we propose a new methodology for constructing adjacent relations in sensor networks using an...
Swarm intelligence deals with the behavior of natural or artificial swarms. Swarms are systems that consist of many individuals that are organized and coordinated by principles of decentralized control, indirect communication, and self-organization. Examples of natural swarms are social insect colonies, flocks of birds, schools of fish, or herds of land animals. Examples of artificial swarms include...
Aimed at resolving the problems of sensitivity to noise and over-segmentation existing in traditional watershed algorithm, we presents a new image segmentation method - combining watersheds and ant colony clustering(CWAC). Firstly, the image is initially segmented using watershed algorithm. Then, ant colony clustering algorithm is used to merge different regions of homogeneity to gain the final result...
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