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METHOD AND SYSTEM FOR CLASSIFYING FUNCTIONAL ALTERNATION PATTERNS OF DEFAULT MODE NETWORK IN PROGRESSION OF NORMAL AGING TO MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE
METHOD AND SYSTEM FOR CLASSIFYING FUNCTIONAL ALTERNATION PATTERNS OF DEFAULT MODE NETWORK IN PROGRESSION OF NORMAL AGING TO MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE
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机译：在正常衰老，轻度认知障碍和老年痴呆症发展过程中对默认模式网络功能替代模式进行分类的方法和系统
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摘要
PURPOSE: A method and system for classifying a functional change pattern of a default mode network according to the progression of Alzheimer's disease are provided to early diagnose a patient by accurately classifying a change pattern of a functional connection of the default mode network. CONSTITUTION: An area with a difference between default mode networks of an Alzheimer's patient, a patient with mild cognitive impairment, and a healthy person over a preset value is extracted (130). Functional connection information about the default mode network is extracted from the extracted area (140). A relation between the extracted functional connection information and dementia classification information showing the progression of dementia is analyzed. A functional change pattern of the default mode network is classified according to the progression of the dementia (150). [Reference numerals] (110) Obtain MRIs of a patient with Alzheimer's, a patient with mild cognitive impairment, and a healthy person; (120) Extract the three groups' default mode networks by performing an independent element analysis process based on the obtained MRIs; (130) Extract areas with larger differences than a previously-set value by performing a covariance analysis process based on the default mode networks of the three groups; (140) Extract functional connection information from the extracted areas; (150) Distinguish the patterns of functional changes in the default mode networks by analyzing the relationship between the extracted functional connection information and Alzheimer's identification information; (AA) Start; (BB) End
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