A physical information neural network-based path planning method for flexible needle puncture of soft tissues

Li Zheng; Fan Zhang; Yeqian Huang; Deng Qianxue; Liu Weikang

doi:10.1080/13645706.2026.2616591

February 5, 2026Minimally Invasive Therapy & Allied Technologies

A physical information neural network-based path planning method for flexible needle puncture of soft tissues

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Key Points

This research aims to improve needle puncture methods using advanced path planning techniques.
Utilized a combined physical information neural network (PINN) with RRT* algorithm.
Addressed modeling complexity in soft tissue puncture.
Focused on real-time adaptability to dynamic conditions.
Reduced dependence on expert techniques for planning.
Significantly improved safety during needle puncture.
Enhanced overall efficiency of the process.
Demonstrated effectiveness in complex modeling scenarios.

Implication

A combined neural network and RRT* method enhances safety and efficiency in needle puncture techniques.

Abstract

The combined PINN-RRT* approach addresses modeling complexity, path planning difficulty, real-time adaptability, and expert dependence in traditional puncture techniques, significantly improving safety and efficiency.

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Cite This Study

Zheng et al. (2026) studied this question.

synapsesocial.com/papers/698828410fc35cd7a884790f https://doi.org/10.1080/13645706.2026.2616591

View Full Paper

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A physical information neural network-based path planning method for flexible needle puncture of soft tissues

Key Points

Implication

Abstract

Discussion

Cite This Study

A physical information neural network-based path planning method for flexible needle puncture of soft tissues

Key Points

Implication

Abstract

Discussion

Cite This Study

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