Demo Data from EDBT 2026 / reviewers in the wild / expert
Jiulong Lan
dblp:216/8186
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-4729-7871ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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 · 100% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
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
medical imaging |
0.4 | 1 | 2019 | Automatic ultrasound scanning system based on robotic arm · Sci. China Inf. Sci. 2019 |
Medical and health informatics › medical imaging › ultrasound imaging
ultrasound scanning |
0.4 | 1 | 2019 | Automatic ultrasound scanning system based on robotic arm · Sci. China Inf. Sci. 2019 |
Robotics › Motion planning and robot control › manipulator control
robot arm control |
0.1 | 1 | 2019 | Automatic ultrasound scanning system based on robotic arm · Sci. China Inf. Sci. 2019 |
Methods — techniques the papers use, named apart from their topics
robotic arm · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Automatic ultrasound scanning system based on robotic arm
Qinghua Huang, Jiulong Lan, Xuelong Li 0001 |
Sci. China Inf. Sci. | 2 |
| 2019 | Robotic Arm Based Automatic Ultrasound Scanning for Three-Dimensional ImagingabstractThis paper presents a human skin inspired automatic robotic ultrasound (US) system for three-dimensional (3-D) imaging. A depth camera was adopted to capture the point cloud of the skin surface. According to the 3-D contour of the skin surface, the scan range and scan path for the US probe could be automatically determined. Then, we used a normal-vector-based method to determine the pose of the robotic arm corresponding to each scan point in the scan path. In addition, two force sensors could feedback the contact force between the scanned tissue and the emission plane of the probe for fine-tuning the pose of the robotic arm. After the scanning, the system could realize 3-D US reconstruction. Experimental results validate the feasibility of the proposed system. It is expected that the proposed system will be useful in clinical practices. Qinghua Huang, Jiulong Lan, Xuelong Li 0001 |
IEEE Trans. Ind. Informatics | 2 |