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学科主题: 临床医学
题名:
DWI-Based Neural Fingerprinting Technology: A Preliminary Study on Stroke Analysis
作者: Ye, Chenfei1; Ma, Heather Ting1; Wu, Jun2; Yang, Pengfei1; Chen, Xuhui2; Yang, Zhengyi3; Ma, Jingbo1
刊名: BIOMED RESEARCH INTERNATIONAL
发表日期: 2014
DOI: 10.1155/2014/725052
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology
类目[WOS]: Biotechnology & Applied Microbiology ; Medicine, Research & Experimental
研究领域[WOS]: Biotechnology & Applied Microbiology ; Research & Experimental Medicine
关键词[WOS]: APPARENT DIFFUSION-COEFFICIENT ; VOXEL-BASED MORPHOMETRY ; APPEARING WHITE-MATTER ; MULTIPLE-SCLEROSIS ; SPATIAL STATISTICS ; WATER DIFFUSION ; WEIGHTED MRI ; TENSOR ; BRAIN ; DEGENERATION
英文摘要:

Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI) has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI) on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.

语种: 英语
所属项目编号: KQC201109020052A ; 81000647 ; JC201005260124A
项目资助者: High-End Talent Overseas Returnees Foundation of Shenzhen ; National Natural Science Foundation of China ; Basic Research Foundation (Outstanding Young Investigator Track) of Shenzhen
WOS记录号: WOS:000340754200001
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/52645
Appears in Collections:北京大学深圳医院_神经内科_期刊论文

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作者单位: 1.Harbin Inst Technol, Shenzhen Grad Sch, Dept Elect & Informat Engn, Shenzhen 518055, Peoples R China
2.Peking Univ, Shenzhen Hosp, Dept Neurol, Shenzhen 18036, Peoples R China
3.Univ Queensland, Sch Informat Technol & Elect Engn, St Lucia, Qld 4072, Australia

Recommended Citation:
Ye, Chenfei,Ma, Heather Ting,Wu, Jun,et al. DWI-Based Neural Fingerprinting Technology: A Preliminary Study on Stroke Analysis[J]. BIOMED RESEARCH INTERNATIONAL,2014.
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