Deep Learning Aided Neuroimaging and Brain Regulation

doi:10.3390/s23114993

UM > Faculty of Health Sciences > DEPARTMENT OF PUBLIC HEALTH AND MEDICINAL ADMINISTRATION

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Status	已發表Published
	Deep Learning Aided Neuroimaging and Brain Regulation
	Xu, Mengze 1,2; Ouyang, Yuanyuan 3,4; Yuan, Zhen2
	2023-06-01
Source Publication	Sensors
ISSN	1424-8220
Volume	23 Issue:11
Abstract	Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier application and the future development trend of precision neuroscience. This review aimed to render comprehensive and informative insights into the recent progress of deep learning and its applications in medical imaging for brain monitoring and regulation. The article starts by providing an overview of the current methods for brain imaging, highlighting their limitations and introducing the potential benefits of using deep learning techniques to overcome these limitations. Then, we further delve into the details of deep learning, explaining the basic concepts and providing examples of how it can be used in medical imaging. One of the key strengths is its thorough discussion of the different types of deep learning models that can be used in medical imaging including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial network (GAN) assisted magnetic resonance imaging (MRI), positron emission tomography (PET)/computed tomography (CT), electroencephalography (EEG)/magnetoencephalography (MEG), optical imaging, and other imaging modalities. Overall, our review on deep learning aided medical imaging for brain monitoring and regulation provides a referrable glance for the intersection of deep learning aided neuroimaging and brain regulation.
Keyword	artificial intelligence brain regulation deep learning medical imaging neuroimaging
DOI	10.3390/s23114993
URL	View the original
Language	英語English
Scopus ID	2-s2.0-85161498621
Fulltext Access	View Full-Text via DOI View Full-Text via Web of Science View Full-Text via Scopus
Citation statistics
Document Type	Journal article
Collection	DEPARTMENT OF PUBLIC HEALTH AND MEDICINAL ADMINISTRATION
Affiliation	1.Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai, 519087, China 2.Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, 999078, Macao 3.Nanomicro Sino-Europe Technology Company Limited, Zhuhai, 519031, China 4.Jiangfeng China-Portugal Technology Co., Ltd, 999078, Macao
First Author Affilication	INSTITUTE OF COLLABORATIVE INNOVATION
Recommended Citation GB/T 7714	Xu, Mengze,Ouyang, Yuanyuan,Yuan, Zhen. Deep Learning Aided Neuroimaging and Brain Regulation[J]. Sensors, 2023, 23(11).
APA	Xu, Mengze., Ouyang, Yuanyuan., & Yuan, Zhen (2023). Deep Learning Aided Neuroimaging and Brain Regulation. Sensors, 23(11).
MLA	Xu, Mengze,et al."Deep Learning Aided Neuroimaging and Brain Regulation".Sensors 23.11(2023).

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