CSpace  > 中国科学院计算技术研究所期刊论文  > 英文
Computer Vision for Brain Disorders Based Primarily on Ocular Responses
Li, Xiaotao1,2,3,4,5; Fan, Fangfang6; Chen, Xuejing7; Li, Juan1,2,4,5; Ning, Li8; Lin, Kangguang9,10; Chen, Zan1,2; Qin, Zhenyun11; Yeung, Albert S.12; Li, Xiaojian1,2; Wang, Liping1,2; So, Kwok-Fai10,13
2021-04-21
发表期刊FRONTIERS IN NEUROLOGY
ISSN1664-2295
卷号12页码:9
摘要Real-time ocular responses are tightly associated with emotional and cognitive processing within the central nervous system. Patterns seen in saccades, pupillary responses, and spontaneous blinking, as well as retinal microvasculature and morphology visualized via office-based ophthalmic imaging, are potential biomarkers for the screening and evaluation of cognitive and psychiatric disorders. In this review, we outline multiple techniques in which ocular assessments may serve as a non-invasive approach for the early detections of various brain disorders, such as autism spectrum disorder (ASD), Alzheimer's disease (AD), schizophrenia (SZ), and major depressive disorder (MDD). In addition, rapid advances in artificial intelligence (AI) present a growing opportunity to use machine learning-based AI, especially computer vision (CV) with deep-learning neural networks, to shed new light on the field of cognitive neuroscience, which is most likely to lead to novel evaluations and interventions for brain disorders. Hence, we highlight the potential of using AI to evaluate brain disorders based primarily on ocular features.
关键词ocular assessment retina computer vision cognitive neuroscience brain disorders eye-brain engineering
DOI10.3389/fneur.2021.584270
收录类别SCI
语种英语
资助项目Key-Area Research and Development Program of Guangdong Province[2018B030331001] ; International Postdoctoral Exchange Fellowship Program by the Office of China Postdoctoral Council[20160021] ; International Partnership Program of Chinese Academy of Sciences[172644KYS820170004] ; Commission on Innovation and Technology in Shenzhen Municipality of China[JCYJ20150630114942262] ; Hong Kong, Macao, and Taiwan Science and Technology Cooperation Innovation Platform in Universities in Guangdong Province[2013gjhz0002] ; National Key R&D Program of China[2017YFC1310503]
WOS研究方向Neurosciences & Neurology
WOS类目Clinical Neurology ; Neurosciences
WOS记录号WOS:000646851700001
出版者FRONTIERS MEDIA SA
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.204/handle/2XEOYT63/17825
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Li, Xiaotao; So, Kwok-Fai
作者单位1.Chinese Acad Sci, Brain Cognit & Brain Dis Inst, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
2.Shenzhen Fundamental Res Inst, Shenzhen Hong Kong Inst Brain Sci, Shenzhen, Peoples R China
3.MIT, Dept Brain & Cognit Sci, E25-618, Cambridge, MA 02139 USA
4.BIAI INC, Chelmsford, MA 01824 USA
5.BIAI Intelligence Biotech LLC, Shenzhen, Peoples R China
6.Harvard Univ, Dept Neurol, Harvard Med Sch, Boston, MA USA
7.Boston Univ, Dept Ophthalmol, Retina Div, Eye Associates, Boston, MA USA
8.Chinese Acad Sci, Ctr High Performance Comp, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
9.Guangzhou Med Univ, Dept Affect Disorders & Academician Workstn Mood, Affiliated Brain Hosp, Guangzhou Huiai Hosp, Guangzhou, Peoples R China
10.Jinan Univ, Guangdong Hong Kong Macau Inst Cent Nervous Syst, Guangzhou, Peoples R China
11.Fudan Univ, Sch Math Sci, Key Lab Nonlinear Math Models & Methods, Shanghai, Peoples R China
12.Massachusetts Gen Hosp, Dept Psychiat, Depress Clin & Res Program, Boston, MA 02114 USA
13.Univ Hong Kong, State Key Lab Brain & Cognit Sci, Dept Ophthalmol, Pok Fu Lam, Hong Kong, Peoples R China
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GB/T 7714
Li, Xiaotao,Fan, Fangfang,Chen, Xuejing,et al. Computer Vision for Brain Disorders Based Primarily on Ocular Responses[J]. FRONTIERS IN NEUROLOGY,2021,12:9.
APA Li, Xiaotao.,Fan, Fangfang.,Chen, Xuejing.,Li, Juan.,Ning, Li.,...&So, Kwok-Fai.(2021).Computer Vision for Brain Disorders Based Primarily on Ocular Responses.FRONTIERS IN NEUROLOGY,12,9.
MLA Li, Xiaotao,et al."Computer Vision for Brain Disorders Based Primarily on Ocular Responses".FRONTIERS IN NEUROLOGY 12(2021):9.
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