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Laura Isabel Hanke

dblp:363/9726 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › medical virtual reality
medical training simulator
0.712023
LiVRSono - Virtual Reality Training with Haptics for Intraoperative Ultrasound · ISMAR 2023
Virtual and augmented reality
virtual reality
0.712023
LiVRSono - Virtual Reality Training with Haptics for Intraoperative Ultrasound · ISMAR 2023
Haptics and multimodal interaction
haptic feedback
0.712023
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
YearPublicationVenuePosition
2023 LiVRSono - Virtual Reality Training with Haptics for Intraoperative Ultrasound
abstract
One 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
ISMAR3