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A Mixed Model Binary Imaging Strategy Using Wireless Sensors for Brain Imaging

Communication Systems and Network Technologies(2011)

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Abstract
Cognitive radio is a new paradigm for wireless communications offering a solution to conciliate the current spectrum demand growth and underutilization without changes to the existing legacy wireless systems. Segmentation of brain structures from MR images is crucial in understanding the disease progress, diagnosis, and treatment monitoring. Atlases, showing the expected locations of the structures, are commonly used to start and guide the segmentation process. Classification of complex motor activities from brain imaging is relatively new in the fields of neuroscience and brain-computer interfaces (BCIs). In many cases, the quality of the atlas may have a significant effect in the final result. In this paper we propose a novel mixed model Binary Imaging Strategy using Wireless Sensors for brain imaging. In this technique we first segmented the images and deform with the manual contour. Our study shows that the expected result is good in various areas.
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Key words
brain imaging,wireless communication,binary imaging strategy,expected result,wireless sensors,existing legacy wireless system,new paradigm,final result,segmentation process,expected location,mixed model binary imaging,brain structure,communication systems,image segmentation,neuroscience,segmentation,decision support systems,image classification,mixed model,neurophysiology,diagnosis,brain computer interfaces,binary image,cognitive radio,wireless sensor networks,brain computer interface
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