Application of Artificial Intelligence in the MRI Classification Task of Human Brain Neurological and Psychiatric Diseases: A Scoping Review

被引：37
作者：
Zhang, Zhao [1 ]
Li, Guangfei [1 ]
Xu, Yong [2 ]
Tang, Xiaoying [1 ]
机构：
[1] Beijing Inst Technol, Sch Life Sci, Dept Biomed Engn, 715-3 Teaching Bldg 5,5 South Zhongguancun Rd, Beijing 100081, Peoples R China
[2] Chinese Peoples Liberat Army Gen Hosp, Dept Cardiol, Beijing 100853, Peoples R China
来源：
DIAGNOSTICS | 2021年 / 11卷 / 08期
基金：
国家重点研发计划;
关键词：
artificial intelligence; machine learning; deep learning; human brain-related diseases; magnetic resonance image; ATTENTION-DEFICIT/HYPERACTIVITY DISORDER; AUTISM SPECTRUM DISORDER; CONVOLUTIONAL NEURAL-NETWORKS; MAJOR DEPRESSIVE DISORDER; LEARNING FRAMEWORK; BIPOLAR DISORDER; CONNECTIVITY; SCHIZOPHRENIA; PREDICTION; RECOGNITION;
D O I：
10.3390/diagnostics11081402
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
Artificial intelligence (AI) for medical imaging is a technology with great potential. An in-depth understanding of the principles and applications of magnetic resonance imaging (MRI), machine learning (ML), and deep learning (DL) is fundamental for developing AI-based algorithms that can meet the requirements of clinical diagnosis and have excellent quality and efficiency. Moreover, a more comprehensive understanding of applications and opportunities would help to implement AI-based methods in an ethical and sustainable manner. This review first summarizes recent research advances in ML and DL techniques for classifying human brain magnetic resonance images. Then, the application of ML and DL methods to six typical neurological and psychiatric diseases is summarized, including Alzheimer's disease (AD), Parkinson's disease (PD), major depressive disorder (MDD), schizophrenia (SCZ), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). Finally, the limitations of the existing research are discussed, and possible future research directions are proposed.
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页数：27
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