Demo Data from EDBT 2026 / reviewers in the wild / expert
Guanyun Liu
dblp:329/2292
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics
computer-assisted intervention |
0.8 | 1 | 2024 | Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues · ICRA 2024 |
Medical and health informatics › computer-assisted surgery
needle insertion |
0.8 | 1 | 2024 | Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer Tissues · ICRA 2024 |
Computational science and engineering
finite element analysis |
0.2 | 1 | 2024 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Bevel-Tip Needle Deflection Modeling, Simulation, and Validation in Multi-Layer TissuesabstractPercutaneous 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 |
ICRA | 3 |