深度学习
人工智能
磁共振成像
神经影像学
计算机科学
脑功能
优势和劣势
任务(项目管理)
功能磁共振成像
神经科学
机器学习
心理学
医学
放射科
工程类
社会心理学
系统工程
作者
Xingzhong Zhao,Xing‐Ming Zhao
出处
期刊:Methods
[Elsevier BV]
日期:2020-09-12
卷期号:192: 131-140
被引量:53
标识
DOI:10.1016/j.ymeth.2020.09.007
摘要
• MRI analysis is critical to both understanding and diagnosis of brain disorders. • We present an overview of the popular deep learning applications in brain MR images. • We discuss the challenge and the future direction of deep learning in brain MR image. Magnetic resonance imaging (MRI) is one of the most popular techniques in brain science and is important for understanding brain function and neuropsychiatric disorders. However, the processing and analysis of MRI is not a trivial task with lots of challenges. Recently, deep learning has shown superior performance over traditional machine learning approaches in image analysis. In this survey, we give a brief review of the recent popular deep learning approaches and their applications in brain MRI analysis. Furthermore, popular brain MRI databases and deep learning tools are also introduced. The strength and weaknesses of different approaches are addressed, and challenges as well as future directions are also discussed.
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