基于力视感知的斜尖柔性针轨迹预测

doi:10.3901/JME.2021.11.052

机械工程学报 ›› 2021, Vol. 57 ›› Issue (11): 52-60.doi: 10.3901/JME.2021.11.052

• 特邀专栏：生物组织精准手术器械设计制造 • 上一篇下一篇

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基于力视感知的斜尖柔性针轨迹预测

王林泽¹, 高德东¹, 白辉全², 赵岩¹, 崔加利³, 李沐蓉⁴, 雷勇⁴

1. 青海大学机械工程学院西宁 810016;
2. 西宁市第一人民医院西宁 810016;
3. 青海大学计算机技术与应用系西宁 810016;
4. 浙江大学流体动力与机电系统国家重点实验室杭州 310027

收稿日期:2020-11-10 修回日期:2021-02-09 出版日期:2021-07-23 发布日期:2021-07-23
通讯作者: 高德东(通信作者),男,1980年出生,博士,教授,博士研究生导师。主要研究方向为计算机辅助医疗工程、新能源智慧运维技术。E-mail:gaodd@zju.edu.cn
作者简介:王林泽,男,1997年出生。主要研究方向为计算机辅助医疗。E-mail:1510559207@qq.com
基金资助:
国家自然科学基金资助项目（51665049）。

Trajectory Prediction of Bevel-Tip Flexible Needle Based on Force and Vision Perception

WANG Linze¹, GAO Dedong¹, BAI Huiquan², ZHAO Yan¹, CUI Jiali³, LI Murong⁴, LEI Yong⁴

1. School of Mechanical Engineering, Qinghai University, Xining 810016;
2. Xining First People's Hospital, Xining 810016;
3. Department of Computer Technology and Application, Qinghai University, Xining 810016;
4. State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027

Received:2020-11-10 Revised:2021-02-09 Online:2021-07-23 Published:2021-07-23

摘要/Abstract

摘要： 在临床应用中，精确控制柔性针到达靶点是一个挑战。在穿刺过程中，作用在柔性针上的力会导致组织变形和针偏转，进而造成针尖错位。针和软组织之间的相互作用涉及大量的生物物理特征，而且这些参数不可能通过物理建模或直接估算得出。为解决这一难题，提出一种预测针尖轨迹的方法。对柔性针进行受力分析，建立力学模型；在力学模型的基础上，建立了一种基于BP神经网络的力视感知预测模型，预测穿刺过程中的针尖轨迹。使用三种不同型号的柔性针进行试验，采集数据并对模型进行训练。最后通过试验得到针尖轨迹，与模型预测进行比较。结果表明，模型预测的针尖在x、y方向的位移与试验结果基本一致，误差在2 mm以内，能够较准确地预测穿刺轨迹。

关键词: 针穿刺, BP神经网络, 软组织, 图像处理

Abstract: It is a challenge to precisely control the flexible needle to reach the target in clinical applications. The force acting on the flexible needle can cause tissue deformation and needle bending, resulting in misalignment of the needle tip. The interaction between the needle and soft tissue involves a large number of biophysical characteristics, and these parameters cannot be estimated through physical modeling or directly. In order to solve this problem, a method to predict the needle trajectory is proposed. The force analysis for the flexible needle is carried out and the corresponding mechanical model is established; on the basis of the mechanical model, a force-vision perception prediction model based on BP neural network is established and needle tip trajectory is predicted. Three different types of flexible needles are tested, data are collected to train the model. Finally, the needle tip trajectory was obtained through experiments, which are compared with the model prediction. The results show that the displacements in x and y directions predicted by the model can accord with the experiments and model error is within 2mm, which can predict the insertion trajectory more accurately.

Key words: needle insertion, BP neural network, soft tissue, image processing

中图分类号:

TH789

王林泽, 高德东, 白辉全, 赵岩, 崔加利, 李沐蓉, 雷勇. 基于力视感知的斜尖柔性针轨迹预测[J]. 机械工程学报, 2021, 57(11): 52-60.

WANG Linze, GAO Dedong, BAI Huiquan, ZHAO Yan, CUI Jiali, LI Murong, LEI Yong. Trajectory Prediction of Bevel-Tip Flexible Needle Based on Force and Vision Perception[J]. Journal of Mechanical Engineering, 2021, 57(11): 52-60.

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基于力视感知的斜尖柔性针轨迹预测

Trajectory Prediction of Bevel-Tip Flexible Needle Based on Force and Vision Perception

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