THE POTENTIAL FIELD-BASED TRAJECTORY PLANNING FOR NEEDLE INSERTION IN A SOFT-TISSUE MODEL

2013 ◽  
Vol 25 (01) ◽  
pp. 1350017
Author(s):  
Shan Jiang ◽  
Zhiliang Su ◽  
Zhiyong Yang ◽  
Jun Liu ◽  
Zhenxing Liu

This paper presents a 3D dynamic trajectory planning method for the insertion of a rigid needle into soft tissue. The optimal needle tip orientation was calculated in which applying an artificial potential field method to determine the 3D distribution of repulsive and attractive forces surrounding the target object and adjacent obstacles, e.g. bones, nerves, or arteries. Soft-tissue deformation occurs dynamically and continuously during the needle insertion. The trajectory planning was therefore temporally discretized, and the compartment searching method used in each time step. This trajectory planning method was then validated by a dynamic finite element method (FEM) simulation. The dynamic finite element model is built for the important displacement parameters of deformation node in needle insertion process. The Mooney–Rivlin material model combined with solid cubic element and an explicit center differencing scheme was used to compute the soft-tissue deformation at each time step and dynamically identify the target and obstacle positions. The proposed trajectory planning method can optimize the insertion path to achieve the target position while avoiding obstacles.

2010 ◽  
Vol 139-141 ◽  
pp. 889-892
Author(s):  
De Dong Gao ◽  
Hao Jun Zheng

Needle deflection and soft tissue deformation are the most important factors that affect accuracy in needle insertion. Based on the quasi-static thinking and needle forces, an improved virtual spring model and a finite element method are presented to analyze needle deflection and soft tissue deformation when a needle is inserted into soft tissue. According to the spring model, the trajectory of the needle tip is calculated with MATLAB using different parameters. With the superposed element method, the two and three dimensional quasi-static finite element models are created to simulate the dynamic process of soft tissue deformation using ANSYS software. The two methods will be available for steering the flexible needle to hit the target and avoid the obstacles precisely in the robot-assisted needle insertion.


2020 ◽  
Author(s):  
Yong Lei ◽  
Murong Li ◽  
Dedong Gao

Abstract The simulation and planning system (SPS) requires accurate and real-time feedback regarding the deformation of soft tissues during the needle insertion procedure. Traditional mechanical-based models such as the finite element method (FEM) are widely used to compute the deformations of soft tissue. However, it is difficult for the FEM or other methods to find a balance between an acceptable image fidelity and real-time deformation feedback due to their complex material properties, geometries and interaction mechanisms. In this paper, a Kriging-based method is applied to model the soft tissue deformation to strike a balance between the accuracy and efficiency of deformation feedback. Four combinations of regression and correlation functions are compared regarding their ability to predict the maximum deformations of ten characteristic markers at a fixed insertion depth. The results suggest that a first order regression function with Gaussian correlation functions can best fit the results of the ground truth. The functional response of the Kriging-based method is utilized to model the dynamic deformations of markers at a series of needle insertion depths. The feasibility of the method is verified by investigating the adaptation to step variations. Compared with the ground truth of the finite element (FE) results, the maximum residual is less than 0.92mm in the Y direction and 0.31mm in the $X$ direction. The results suggest that the Kriging metamodel provides real-time deformation feedback for a target and an obstacle to a SPS.


2003 ◽  
Vol 2003 (0) ◽  
pp. 641-642
Author(s):  
Toshikatsu Washio ◽  
Kiyoshi Yoshinaka ◽  
Kiyoyuki Chinzei ◽  
Kazuyuki Mizuhara

1992 ◽  
Vol 34 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Mitsuru MOTOYOSHI ◽  
Shigemi YAMAMURA ◽  
Akira NAKAJIMA ◽  
Akihiko YOSHIZUMI ◽  
Yoshinari UMEMURA ◽  
...  

2008 ◽  
Vol 2008.6 (0) ◽  
pp. 101-102
Author(s):  
Hiroyuki KATAOKA ◽  
Shigeho NODA ◽  
Hideo YOKOTA ◽  
Shu TAKAGI ◽  
Ryutaro HIMENO ◽  
...  

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