Demo Data from SIGIR 2026 / reviewers in the wild / expert
Laura Isabel Hanke
dblp:363/9726
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 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.
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Haptics and multimodal interaction · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › medical virtual reality
medical training simulator |
0.7 | 1 | 2023 | LiVRSono - Virtual Reality Training with Haptics for Intraoperative Ultrasound · ISMAR 2023 |
Virtual and augmented reality
virtual reality |
0.7 | 1 | 2023 | LiVRSono - Virtual Reality Training with Haptics for Intraoperative Ultrasound · ISMAR 2023 |
Haptics and multimodal interaction
haptic feedback |
0.7 | 1 | 2023 | LiVRSono - Virtual Reality Training with Haptics for Intraoperative Ultrasound · ISMAR 2023 |
Methods — techniques the papers use, named apart from their topics
ultrasound simulation · 2.0patient-specific data · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | LiVRSono - Virtual Reality Training with Haptics for Intraoperative UltrasoundabstractOne of the biggest challenges in using ultrasound (US) is learning to create a spatial mental model of the interior of the scanned object based on the US image and the probe position. As intraoperative ultrasound (IOUS) cannot be easily trained on patients, we present LiVRSono, an immersive VR application to train this skill. The immersive environment, including an US simulation with patientspecific data as well as haptics to support hand-eye coordination, provides a realistic setting. Four clinically relevant training scenarios were identified based on the described learning goal and the workflow of IOUS for liver. The realism of the setting and the training scenarios were evaluated with eleven physicians, of which six participants are experts in IOUS for liver and five participants are potential users of the training system. The setting, handling of the US probe, and US image were considered realistic enough for the learning goal. Regarding the haptic feedback, a limitation is the restricted workspace of the input device. Three of the four training scenarios were rated as meaningful and effective. A pilot study regarding learning outcome shows positive results, especially with respect to confidence and perceived competence. Besides the drawbacks of the input device, our training system provides a realistic learning environment with meaningful scenarios to train the creation of a mental 3D model when performing IOUS. We also identified important improvements to the training scenarios to further enhance the training experience. Mareen Allgaier, Florentine Huettl, Laura Isabel Hanke, Hauke Lang, Tobias Huber, Bernhard Preim, Sylvia Saalfeld, Christian Hansen 0001 |
ISMAR | 3 |