功能性磁共振成像在轻度认知障碍检测诊断的研究综述

doi:10.3969/j.issn.0258-8021.2022.01.011

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Abstract Nowadays Alzheimer's disease (AD) has severely influenced and limited personal daily life and even posed a grave threat to the life and health of patients. Mild cognitive impairment (MCI) is the prodromal stage of AD, and accurate diagnosis can help to interfere or reduce the conversion of patients to Alzheimer's disease. At present, functional magnetic resonance imaging (fMRI) technology have been widely used in the detection and diagnosis of MCI. This article introduced the research status of fMRI in MCI from the aspects of feature extraction, feature selection, data dimensionality reduction and classification recognition. First, the commonly used resolution indicators such as low-frequency amplitude, local consistency, and functional connection for feature extraction was introduced. Second, features selection and data dimension reduction methods were introduced, and the efficient machine learning and deep learning algorithms in classification and recognition were summarized. This paper also proposed the remained problems and made perspectives to the future research.

Key words： mild cognitive impairment Alzheimer's disease functional magnetic resonance imaging(fMRI) machine learning classification

Received: 27 July 2020

PACS:

R318

Corresponding Authors: ^* E-mail: richardming@tju.edu.cn

About author:: ^#Member, Chinese Society of Biomedical Engineering

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	An Xingwei
	Zhou Yutao
	Di Yang
	Liu Shuang
	Ming Dong

Cite this article:

An Xingwei,Zhou Yutao,Di Yang, et al. Review of Functional Magnetic Resonance Imagingin Diagnosis of Mild Cognitive Impairment[J]. Chinese Journal of Biomedical Engineering, 2022, 41(1): 100-107.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2022.01.011 OR http://cjbme.csbme.org/EN/Y2022/V41/I1/100

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