Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review

Jin，Richu1,2; Cai，Yongning1; Zhang，Shiyang2; Yang，Ting2; Feng，Haibo2; Jiang，Hongyang2; Zhang，Xiaoqing2; Hu，Yan2; Liu，Jiang1,2,3

2023

10.3389/fnins.2023.1191999

Frontiers in Neuroscience   Impact Factor & Quartile

1662-4548

1662-453X

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.

artificial intelligence fiber tracking image segmentation medical image analysis optic nerve fiber visual pathway

SCI

English

First ; Corresponding

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]

Neurosciences & Neurology

Neurosciences

WOS:001003123100001

FRONTIERS MEDIA SA

2-s2.0-85161427109

Scopus

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

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.

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.

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).