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使用结构光相机的自动机器人辅助宽视野光学相干断层扫描

Automated robot-assisted wide-field optical coherence tomography using structured light camera.

作者信息

Li Xiaochen, Huang Yong, Hao Qun

机构信息

School of Optics and Photonics, Beijing Institute of Technology, No.5 South Zhongguancun Street, Haidian, Beijing, 100081, China.

出版信息

Biomed Opt Express. 2023 Jul 26;14(8):4310-4325. doi: 10.1364/BOE.496710. eCollection 2023 Aug 1.

Abstract

Optical coherence tomography (OCT) is a promising real-time and non-invasive imaging technology widely utilized in biomedical and material inspection domains. However, limited field of view (FOV) in conventional OCT systems hampers their broader applicability. Here, we propose an automated system integrating a structured light camera and robotic arm for large-area OCT scanning. The system precisely detects tissue contours, automates scan path generation, and enables accurate scanning of expansive sample areas. The proposed system consists of a robotic arm, a three-dimensional (3D) structured light camera, and a customized portable OCT probe. The 3D structured light camera is employed to generate a precise 3D point cloud of the sample surface, enabling automatic planning of the scanning path for the robotic arm. Meanwhile, the OCT probe is mounted on the robotic arm, facilitating scanning of the sample along the predetermined path. Continuous OCT B-scans are acquired during the scanning process, facilitating the generation of high-resolution and large-area 3D OCT reconstructions of the sample. We conducted position error tests and presented examples of 3D macroscopic imaging of different samples, such as kidney, skin and leaf blade. The robotic arm can accurately reach the planned positions with an average absolute error of approximately 0.16 mm. The findings demonstrate that the proposed system enables the acquisition of 3D OCT images covering an area exceeding 20 cm, indicating wide-ranging potential for utilization in diverse domains such as biomedical, industrial, and agricultural fields.

摘要

光学相干断层扫描(OCT)是一种很有前景的实时无创成像技术,广泛应用于生物医学和材料检测领域。然而,传统OCT系统有限的视野(FOV)阻碍了它们更广泛的应用。在此,我们提出一种集成结构光相机和机器人手臂的自动化系统,用于大面积OCT扫描。该系统能精确检测组织轮廓,自动生成扫描路径,并能对大面积样本区域进行精确扫描。所提出的系统由一个机器人手臂、一个三维(3D)结构光相机和一个定制的便携式OCT探头组成。3D结构光相机用于生成样本表面精确的3D点云,从而为机器人手臂自动规划扫描路径。同时,OCT探头安装在机器人手臂上,便于沿预定路径对样本进行扫描。在扫描过程中获取连续的OCT B扫描图像,有助于生成样本的高分辨率大面积3D OCT重建图像。我们进行了位置误差测试,并展示了不同样本(如肾脏、皮肤和叶片)的3D宏观成像示例。机器人手臂能够精确到达计划位置,平均绝对误差约为0.16毫米。研究结果表明,所提出的系统能够获取覆盖面积超过20平方厘米的3D OCT图像,表明其在生物医学、工业和农业等不同领域具有广泛的应用潜力。

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