Demo Data from EDBT 2026 / reviewers in the wild / expert
Naner Li
dblp:383/4571
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 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.
| Artificial intelligence
1 paper |
Robot manipulation · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › image-guided intervention
endovascular intervention |
0.2 | 1 | 2024 | Vascular Centerline-Guided Autonomous Navigation Methods for Robot-Lead Endovascular Interventions · ICRA 2024 |
Methods — techniques the papers use, named apart from their topics
electromagnetic tracking · 1.5dynamic time warping · 1.5centerline-guided navigation · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Vascular Centerline-Guided Autonomous Navigation Methods for Robot-Lead Endovascular InterventionsabstractIn minimally invasive endovascular interventional surgery, guidewire navigation is an indispensable process. However, even experienced physicians often encounter difficulties in manually manipulating the guidewire for branch selection, while also facing the risk of radiation exposure. In this study, we investigated robotic autonomous guidewire navigation methods. An electromagnetic system was used to track the real-time position and orientation of the guidewire tip, and a state space representing the guidewire within the vascular environment was constructed to guide the robot in precise guidewire manipulation. Experimental results demonstrated that the proposed trial-and-error and centerline-guided methods successfully completed navigation tasks in a static environment, outperforming human navigation performance in terms of trajectory smoothness, trajectory length, and incorrect branch entry counts. For dynamic environment navigation, dynamic time warping (DTW), a technique for measuring the similarity between two temporal sequences, was integrated into the centerline-guided method. The proposed approaches eliminate the need for visual feedback and thereby minimizing the risk of radiation exposure for both patients and medical staff present in the operating room during the procedure. Naner Li, Yiwei Wang 0002, Haoyuan Cheng, Huan Zhao 0001, Han Ding 0001 |
ICRA | 1 |