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Guanyun Liu

dblp:329/2292 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0002-9149-2332ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 87% Computational science and engineering · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Medical and health informatics
computer-assisted intervention
0.812024
Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues · ICRA 2024
Medical and health informatics › computer-assisted surgery
needle insertion
0.812024
Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues · ICRA 2024
Computational science and engineering
finite element analysis
0.212024
Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues · ICRA 2024

Methods — techniques the papers use, named apart from their topics

mechanics-based modeling · 0.8finite element method · 0.8
YearPublicationVenuePosition
2024 Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues
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.
Yanzhou Wang, Lidia Al-Zogbi, Guanyun Liu, Junichi Tokuda, Axel Krieger, Iulian Iordachita
ICRA3