ArticlePloS one2021
3D virtual reality vs. 2D desktop registration user interface comparison.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 25 citations in OpenAlex.
- Cell Type Populations for 3D Anatomical Structures of the Human Reference Atlas.Scientific data · 2026Article
- Constructing and Using Cell Type Populations of the Human Reference Atlas.bioRxiv : the preprint server for biology · 2025Article
- Segmentation of human functional tissue units in support of a Human Reference Atlas.Communications biology · 2023Article
- Specimen, biological structure, and spatial ontologies in support of a Human Reference Atlas.Scientific data · 2023Article
- The HRA Organ Gallery Affords Immersive Superpowers for Building and Exploring the Human Reference Atlas with Virtual Reality.bioRxiv : the preprint server for biology · 2023Article
- The HRA Organ Gallery affords immersive superpowers for building and exploring the Human Reference Atlas with virtual reality.Frontiers in bioinformatics · 2023Article
- Tissue registration and exploration user interfaces in support of a human reference atlas.Communications biology · 2022Article
- Optimizing Performance and Satisfaction in Matching and Movement Tasks in Virtual Reality with Interventions Using the Data Visualization Literacy Framework.Frontiers in virtual reality · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Working with organs and extracted tissue blocks is an essential task in many medical surgery and anatomy environments. In order to prepare specimens from human donors for further analysis, wet-bench workers must properly dissect human tissue and collect metadata for downstream analysis, including information about the spatial origin of tissue. The Registration User Interface (RUI) was developed to allow stakeholders in the Human Biomolecular Atlas Program (HuBMAP) to register tissue blocks-i.e., to record the size, position, and orientation of human tissue data with regard to reference organs. 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, with planned support for 17 organs in the near future. 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 which is replicated in virtual space; VR Standup, where users stand upright while performing their tasks. All three setups were implemented using the Unity game engine. We then ran a user study for these three setups involving 42 human subjects completing 14 increasingly difficult and then 30 identical tasks in sequence and reporting position accuracy, rotation accuracy, completion time, and satisfaction. All study materials were made available in support of future study replication, alongside videos documenting our setups. 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 (for the sequence of 30 identical tasks), there are no significant differences between the three setups for position accuracy when normalized by the height of the virtual kidney across setups. When extrapolating from the 2D Desktop setup with a 113-mm-tall kidney, the absolute performance values for the 2D Desktop version (22.6 seconds per task, 5.88 degrees rotation, and 1.32 mm position accuracy after 8.3 tasks in the series of 30 identical tasks) confirm that the 2D Desktop interface is well-suited for allowing users in HuBMAP to register 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.