题名 | Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review |
作者 | |
通讯作者 | Jin,Richu; Liu,Jiang |
发表日期 | 2023
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DOI | |
发表期刊 | |
ISSN | 1662-4548
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EISSN | 1662-453X
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卷号 | 17 |
摘要 | Optic never fibers in the visual pathway play significant roles in vision formation. Damages of optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and neurological diseases; also, there is a need to prevent the optic nerve fibers from getting damaged in neurosurgery and radiation therapy. Reconstruction of optic nerve fibers from medical images can facilitate all these clinical applications. Although many computational methods are developed for the reconstruction of optic nerve fibers, a comprehensive review of these methods is still lacking. This paper described both the two strategies for optic nerve fiber reconstruction applied in existing studies, i.e., image segmentation and fiber tracking. In comparison to image segmentation, fiber tracking can delineate more detailed structures of optic nerve fibers. For each strategy, both conventional and AI-based approaches were introduced, and the latter usually demonstrates better performance than the former. From the review, we concluded that AI-based methods are the trend for optic nerve fiber reconstruction and some new techniques like generative AI can help address the current challenges in optic nerve fiber reconstruction. |
关键词 | |
相关链接 | [Scopus记录] |
收录类别 | |
语种 | 英语
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学校署名 | 第一
; 通讯
|
资助项目 | National Natural Science Foundation of China["62101236","82102189"]
; General Program of National Natural Science Foundation of China[82272086]
; Guangdong Provincial Department of Education[2020ZDZX3043]
; Guangdong Provincial Key Laboratory[2020B121201001]
; Shenzhen Natural Science Fund[JCYJ20200109140820699]
; Stable Support Plan Program[20200925174052004]
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WOS研究方向 | Neurosciences & Neurology
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WOS类目 | Neurosciences
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WOS记录号 | WOS:001003123100001
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出版者 | |
Scopus记录号 | 2-s2.0-85161427109
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来源库 | Scopus
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引用统计 |
被引频次[WOS]:0
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成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/560290 |
专题 | 工学院_斯发基斯可信自主研究院 工学院_计算机科学与工程系 |
作者单位 | 1.Research Institute of Trustworthy Autonomous Systems,Southern University of Science and Technology,Shenzhen,China 2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China 3.Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China |
第一作者单位 | 斯发基斯可信自主系统研究院; 计算机科学与工程系 |
通讯作者单位 | 斯发基斯可信自主系统研究院; 计算机科学与工程系 |
第一作者的第一单位 | 斯发基斯可信自主系统研究院 |
推荐引用方式 GB/T 7714 |
Jin,Richu,Cai,Yongning,Zhang,Shiyang,et al. Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review[J]. Frontiers in Neuroscience,2023,17.
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APA |
Jin,Richu.,Cai,Yongning.,Zhang,Shiyang.,Yang,Ting.,Feng,Haibo.,...&Liu,Jiang.(2023).Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review.Frontiers in Neuroscience,17.
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MLA |
Jin,Richu,et al."Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review".Frontiers in Neuroscience 17(2023).
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条目包含的文件 | 条目无相关文件。 |
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