Abstract
In Virtual Reality (VR), locomotion methods allow users to adjust their location in the virtual environment. These methods are sometimes used in 3D-VR medical image manipulation, which has gained interest in VR in the medical field due to the immersive environment and increased number of possible interaction techniques. However, the medical 3D-VR image manipulation context differs from typical VR locomotion, as the focus is not on the navigation of the VR space, but rather on the point of view of the user to the 3D image. For this study, we recruited 24 participants to find and observe easy targets from simplified medical images. We compared whether the three VR locomotion methods, Diving, Grabbing and Teleporting, were suitable for medical 3D image manipulation tasks. Diving was found to be significantly more successful than Teleporting while being an equally fast method. Locomotion method preferences varied. Therefore, a VR system is suggested to provide various manipulation methods for the user. However, the methods need development before they can be used with radiologists for actual medical image analysis tasks. We fill a research gap from the VR medical image manipulation context, where even though VR locomotion methods, such as Teleporting have been sometimes used, there has been a lack of interaction technique studies of these methods. Therefore, we provide necessary data on locomotion methods for the designers and developers of 3D-VR medical image applications. This is an initial study to validate different techniques for medical image analysis tasks in VR.
| Original language | English |
|---|---|
| Pages (from-to) | 105-119 |
| Number of pages | 15 |
| Journal | Interacting with Computers |
| Volume | 37 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Mar 2025 |
| MoE publication type | A1 Journal article-refereed |
Funding
The authors wish to thank members of the TAUCHI research center for help in preparing the experiment. This work has been funded by the Academy of Finland, project Explainable AI Technologies for Segmenting 3D Imaging Data (decision number 345448).
Keywords
- 3d model
- locomotion method
- medical image
- virtual reality
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