用于软组织外科手术的创新机电工具和系统的研究

P. Brett, B. Allotta, J. Wahrburg, V. Petridis
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引用次数: 3

摘要

关注与变形组织相关的侵入性手术工具的控制。解决方案涉及组织界面的受控穿透、组织识别方法和组织位置的控制。解释方法需要预测框架的变形行为,并使用传感数据的特征来实现这一目标。状态的自动解释使工具策略的自动选择和缩放成为可能。研究表明,在如此复杂的工作环境中,参考模型可以成功地用于确定状态,此外,神经网络也可以用于实现相同的目标。在后一种情况下,已经开发并实施了从最小数据集学习的独特方法。该项目为该研究领域提供了重要的线索,并提供了将机电一体化工具部署到广泛的精密外科手术中的潜力。在大多数情况下,当刀具接近体内的目标位置时,刀具作用下组织的偏转或变形是显著的,并且通常是质量结果不可接受的。众所周知,扫描仪的操作精度很高,该项目的结果提供了控制工具运动的技术,以达到类似的工作精度,同时考虑到组织的运动。本文介绍了四种外科手术的机电一体化系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on innovative mechatronic tools and systems for surgical procedures involving soft tissues
Concerns the control of invasive surgical tools relative to deforming tissues. The solutions deal with the controlled penetration of tissue interfaces, tissue discrimination methods and the control of tissue position. Interpretation methods require anticipation of the deformation behaviour of frames and use features that are characteristic of the sensory data to achieve this. Automated interpretation of state enables automatic selection and scaling of tool strategy. It is shown through the study that reference models can be used successfully to determine the state in such complex working environments and, in addition, that neural networks can also be applied to achieve the same goals. In the latter case unique methods for learning from a minimal data set have been developed and implemented. The project has provided significant leads in this research field and provides the potential to deploy mechatronics tools to a wide range of precision surgical procedures. In most situations when a tool approaches a target position in the body the deflection or deformation of tissues under tool action is significant and is often unacceptable for quality results. It is known that scanners operate with great precision and the results of this project offer techniques to control tool movement to a similar working accuracy whilst taking into account movement of tissue. The article presents mechatronic systems for 4 surgical procedures.
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