Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues
November 29, 2023 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Yanzhou Wang, Lidia Al-Zogbi, Guanyun Liu, Jiawei Liu, Junichi Tokuda, Axel Krieger, Iulian Iordachita
arXiv ID
2311.18075
Category
cs.RO: Robotics
Citations
9
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
Abstract
Percutaneous needle insertions are commonly performed for diagnostic and therapeutic purposes as an effective alternative to more invasive surgical procedures. However, the outcome of needle-based approaches relies heavily on the accuracy of needle placement, which remains a challenge even with robot assistance and medical imaging guidance due to needle deflection caused by contact with soft tissues. In this paper, we present a novel mechanics-based 2D bevel-tip needle model that can account for the effect of nonlinear strain-dependent behavior of biological soft tissues under compression. Real-time finite element simulation allows multiple control inputs along the length of the needle with full three-degree-of-freedom (DOF) planar needle motions. Cross-validation studies using custom-designed multi-layer tissue phantoms as well as heterogeneous chicken breast tissues result in less than 1mm in-plane errors for insertions reaching depths of up to 61 mm, demonstrating the validity and generalizability of the proposed method.
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