Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method

Jia Meng; Lingxi Zhou; Shuhao Qian; Chuncheng Wang; Zhe Feng; Shenyi Jiang; Rushan Jiang; Zhihua Ding; Jun Qian; Shuangmu Zhuo; Zhiyi Liu

doi:10.1117/1.JBO.27.10.105003

22 October 2022 Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method

Jia Meng, Lingxi Zhou, Shuhao Qian, Chuncheng Wang, Zhe Feng, Shenyi Jiang, Rushan Jiang, Zhihua Ding, Jun Qian, Shuangmu Zhuo, Zhiyi Liu

Author Affiliations +

Journal of Biomedical Optics, Vol. 27, Issue 10, 105003 (October 2022). https://doi.org/10.1117/1.JBO.27.10.105003

Abstract

Significance

Deep-imaging of cerebral vessels and accurate organizational characterization are vital to understanding the relationship between tissue structure and function.

Aim

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.

Approach

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.

Results

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.

Conclusions

We built an imaging and analysis system for cerebrovasculature that is conducive to applications in neuroscience and clinical fields.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Jia Meng, Lingxi Zhou, Shuhao Qian, Chuncheng Wang, Zhe Feng, Shenyi Jiang, Rushan Jiang, Zhihua Ding, Jun Qian, Shuangmu Zhuo, and Zhiyi Liu "Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method," Journal of Biomedical Optics 27(10), 105003 (22 October 2022). https://doi.org/10.1117/1.JBO.27.10.105003

Received: 22 July 2022; Accepted: 12 October 2022; Published: 22 October 2022

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