Abstract
Nowadays, robust image processing and intelligent systems have gained much popularity and importance in several fields o studies; Consequently, the use of Multi-agent systems (MAS) has been adopted as a strength paradigm for analyzing images. Since, medical image segmentation faces multiple obstacles, the use of MAS has proved precious benefits to accomplish many tasks such as quantification of tissue volumes, medical diagnosis, anatomical structure studies, treatment planning, etc. Currently, diagnosis of Alzheimer Disease (AD) can be made by different methods, neuroimaging assessments are the most used one. Meanwhile, Magnetic Resonance Imaging (MRI) offers well-defined measurement of brain structures, it has been considered as one of the best neuroimaging examination for AD. For this reason, MAS adopt the decentralization of knowledge and behavior in order to provide a powerful resolution of segmentation issues. We briefly describe a framework for Agent Based modeling (ABM) which is designed to 3D image processing especially Alzheimer MRI analysis, and highlights its important characteristics: agent behavior, perception, interactions, cooperation, and negotiation.
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Allioui, H., Sadgal, M., El Faziki, A. (2019). Alzheimer Detection Based on Multi-Agent Systems: An Intelligent Image Processing Environment. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2018). AI2SD 2018. Advances in Intelligent Systems and Computing, vol 914. Springer, Cham. https://doi.org/10.1007/978-3-030-11884-6_28
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DOI: https://doi.org/10.1007/978-3-030-11884-6_28
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