Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method
- Resource Type
- Authors
- Jia, Meng; Lingxi, Zhou; Shuhao, Qian; Chuncheng, Wang; Zhe, Feng; Shenyi, Jiang; Rushan, Jiang; Zhihua, Ding; Jun, Qian; Shuangmu, Zhuo; Zhiyi, Liu
- Source
- Journal of Biomedical Optics. 27
- Subject
- Diagnostic Imaging
Biomaterials
Mice
Photons
Biomedical Engineering
Animals
Brain
Fluorescence
Algorithms
Atomic and Molecular Physics, and Optics
Electronic, Optical and Magnetic Materials
- Language
- ISSN
- 1083-3668
Deep-imaging of cerebral vessels and accurate organizational characterization are vital to understanding the relationship between tissue structure and function.We aim at large-depth imaging of the mouse brain vessels based on aggregation-induced emission luminogens (AIEgens), and we create a new algorithm to characterize the spatial orientation adaptively with superior accuracy.Assisted by AIEgens with near-infrared-II excitation, three-photon fluorescence (3PF) images of large-depth cerebral blood vessels are captured. A window optimizing (WO) method is developed for highly accurate, automated 2D/3D orientation determination. The application of this system is demonstrated by establishing the orientational architecture of mouse cerebrovasculature down to the millimeter-level depth.The WO method is proved to have significantly higher accuracy in both 2D and 3D cases than the method with a fixed window size. Depth- and diameter-dependent orientation information is acquired based on in vivo 3PF imaging and the WO analysis of cerebral vessel images with a penetration depth of 800 μm in mice.We built an imaging and analysis system for cerebrovasculature that is conducive to applications in neuroscience and clinical fields.