期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：11
页码：365-371
出版社：Science and Information Society (SAI)
摘要：The learning techniques have a particular need
especially for the detection of invisible brain diseases. Learningbased
methods rely on MRI medical images to reconstruct a
solution for detecting aberrant values or areas in the human
brain. In this article, we present a method that automatically
performs segmentation of the brain to detect brain damage and
diagnose Alzheimer's disease (AD). In order to take advantages
of the benefits of 3D and reduce complexity and computational
costs, we present a 2.5D method for locating brain inflammation
and detecting their classes. Our proposed system is evaluated on
a set of public data. Preliminary results indicate the reliability
and effectiveness of our Alzheimer's Disease Detection System
and demonstrate that our method is beyond current knowledge
of Alzheimer's disease diagnosis.
