Comparing Completion Time, Accuracy, and Satisfaction in Virtual Reality vs. Desktop Implementation of the Common Coordinate Framework Registration User Interface (CCF RUI)

Authors: Andreas Bueckle, Kilian Buehling, Patrick C. Shih, Katy Börner

34 pages/9 figures in main text; 6 pages/1 figure/2 tables in Supporting Information
License: CC BY 4.0

Abstract: Working with organs and tissue blocks is an essential task in medical environments. In order to prepare specimens for further analysis, wet-bench workers must dissect tissue and collect spatial metadata. The Registration User Interface (RUI) was developed to allow stakeholders in the Human Biomolecular Atlas Program (HuBMAP) to register tissue blocks by size, position, and orientation. The RUI has been used by tissue mapping centers across the HuBMAP consortium to register a total of 45 kidney, spleen, and colon tissue blocks. In this paper, we compare three setups for registering one 3D tissue block object to another 3D reference organ (target) object. The first setup is a 2D Desktop implementation featuring a traditional screen, mouse, and keyboard interface. The remaining setups are both virtual reality (VR) versions of the RUI: VR Tabletop, where users sit at a physical desk; VR Standup, where users stand upright. We ran a user study involving 42 human subjects completing 14 increasingly difficult and then 30 identical tasks and report position accuracy, rotation accuracy, completion time, and satisfaction. We found that while VR Tabletop and VR Standup users are about three times as fast and about a third more accurate in terms of rotation than 2D Desktop users, there are no significant differences for position accuracy. The performance values for the 2D Desktop version (22.6 seconds per task, 5.9 degrees rotation, and 1.32 mm position accuracy) confirm that the 2D Desktop interface is well-suited for registering tissue blocks at a speed and accuracy that meets the needs of experts performing tissue dissection. In addition, the 2D Desktop setup is cheaper, easier to learn, and more practical for wet-bench environments than the VR setups. All three setups were implemented using the Unity game engine, and study materials were made available, alongside videos documenting our setups.

Submitted to arXiv on 24 Feb. 2021

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