用于临床前立体定向神经外科的精密机器人辅助植入

S. Abbaszadeh, Wu Hch
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引用次数: 0

摘要

在立体定向神经外科手术过程中,针的插入或电极/插管/光纤的植入需要快速、精确、准确地识别插入位置,并正确引导针准确到达目标。在这项研究中,我们研究了一种自动化方法来定位感兴趣区域的入口点。该方法利用了数字图像捕获系统、模式识别和机动阶段。基于区域的卷积神经网络和已知解剖可识别区域的模板匹配用于在啮齿动物中寻找感兴趣的区域(例如Bregma)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precision Robotic-Assisted Implantation for Preclinical StereotacticNeurosurgery
During stereotactic neurosurgery procedures, needle insertion or implantation of electrode/cannula/optic fibre requires quick, precise, and accurate identification of insertion location and proper guidance of the needle to accurately reach the target. In this study, we investigate an automated method to locate the entry point of the region of interest. This method leverages a digital image capture system, pattern recognition, and motorized stages. Region-based convolutional neural network and template matching of known anatomical identifiable regions is used to find regions of interest (e.g., Bregma) in rodents.
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