机器人组织扫描与生物光子探针

Lauren Yates, Laura Connolly, A. Jamzad, Mark Asselin, Rachel Rubino, S. Yam, T. Ungi, A. Lasso, C. Nicol, P. Mousavi, G. Fichtinger
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引用次数: 0

摘要

目的:拉曼光谱是一种通过分子分析来表征组织的光学成像技术。使用拉曼光谱进行实时术中组织分类需要在最小的人为干预下进行快速分析。为了进行准确的预测和分类,需要一个具有光谱结果的大型可靠的组织分类数据库。我们已经开发了一个系统,可以用来生成一个有效的扫描路径,机器人扫描组织使用拉曼光谱。方法:安装在机器人控制器上的相机用于拍摄组织载玻片的图像。识别样本图像内组织载玻片的角,并计算载玻片的大小。将图像裁剪以适合幻灯片的大小,并对图像进行处理以识别组织轮廓。计算适合组织大小的网格集,并生成网格扫描模式。组织轮廓的掩膜图像用于创建仅包含组织的扫描模式。将组织扫描模式点转换为机器人控制器坐标系,用于机器人组织扫描。使用组织样本的光谱扫描来验证该模式。将组织扫描模式的运行时间与使用机器人控制器封装组织的感兴趣扫描模式区域进行比较。结果:与感兴趣区扫描相比,组织扫描模式的平均扫描时间缩短了4分58秒。结论:该方法减少了自动机器人扫描所用的点数,可减少扫描时间和不可用数据点,提高数据采集效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robotic tissue scanning with biophotonic probe
PURPOSE: Raman spectroscopy is an optical imaging technique used to characterize tissue via molecular analysis. The use of Raman spectroscopy for real-time intraoperative tissue classification requires fast analysis with minimal human intervention. In order to have accurate predictions and classifications, a large and reliable database of tissue classifications with spectra results is required. We have developed a system that can be used to generate an efficient scanning path for robotic scanning of tissues using Raman spectroscopy. METHODS: A camera mounted to a robotic controller is used to take an image of a tissue slide. The corners of the tissue slides within the sample image are identified, and the size of the slide is calculated. The image is cropped to fit the size of the slide and the image is manipulated to identify the tissue contour. A grid set to fit around the size of the tissue is calculated and a grid scanning pattern is generated. A masked image of the tissue contour is used to create a scanning pattern containing only the tissue. The tissue scanning pattern points are transformed to the robot controller coordinate system and used for robotic tissue scanning. The pattern is validated using spectroscopic scans of the tissue sample. The run time of the tissue scan pattern is compared to a region of interest scanning pattern encapsulating the tissue using the robotic controller. RESULTS: The average scanning time for the tissue scanning pattern compared to region of interest scanning reduced by 4 minutes and 58 seconds. CONCLUSION: This method reduced the number of points used for automated robotic scanning, and can be used to reduce scanning time and unusable data points to improve data collection efficiency.
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