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A Novel Full Prediction Model of 3D Needle Insertion Procedures

  • Murong Li
  • , Yong Lei
  • , Shilun Du
  • , Yingda Hu
  • , Zhen Wang
  • , Tian Xu
  • , Wei Song*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Needle-tissue interaction deformation model can provide the future interaction deformation prediction which can be used to establish the virtual surgery training platform. The prediction information can be used to assist needle path planning scheme. However, existing models either only model the global coupled deformation without force prediction module or model the local contact mechanism between the needle and tissue. The calculation efficiency of the contact mechanism based model limits its application in needle path planning task. In this paper, a novel full prediction model of 3D needle insertion procedures was proposed. The Kriging model can realize fast calculation of the friction force, which is coupled to the 3D needle-tissue coupled deformation model. The local constraint method is applied to avoid the reconstruction of stiffness matrix in each step. The model can simultaneously predict tissue deformation, needle deflection and the interaction force with an acceptable calculation efficiency. The simulation results demonstrate the accuracy of the Kriging based friction force model. The visual simulation results of needle insertion process was also given in this paper. The simulation calculation speed (with an average run time of 30 s) demonstrates the feasibility of its application to needle path planning schemes.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings
EditorsHuayong Yang, Jun Zou, Geng Yang, Xiaoping Ouyang, Honghai Liu, Zhiyong Wang, Zhouping Yin, Lianqing Liu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages173-186
Number of pages14
ISBN (Print)9789819964888
DOIs
StatePublished - 2023
Externally publishedYes
Event16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 - Hangzhou, China
Duration: 5 Jul 20237 Jul 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14269 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Intelligent Robotics and Applications, ICIRA 2023
Country/TerritoryChina
CityHangzhou
Period5/07/237/07/23

Keywords

  • Kriging model
  • full prediction model
  • local constrained method
  • needle insertion

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