Evidence map›Paper›PMID 41820598›Full record

ArticleCommunications engineering2026

SparStVR - exploring sparse 3D histology data in virtual reality.

Kaisa Liimatainen, Leena Latonen, Pekka Ruusuvuori

Abstract read
In one paragraph

Article in Communications engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kaisa LiimatainenFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Leena LatonenInstitute of Biomedicine, University of Eastern Finland, Kuopio, Finland.ORCID http://orcid.org/0000-0003-4502-2193
Pekka RuusuvuoriFaculty of Medicine and Health Technology, Tampere University, Tampere, Finland. pekka.ruusuvuori@utu.fi.ORCID http://orcid.org/0000-0001-9086-9591

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visualization of three-dimensional image stacks from serial sectioned histology or from other modalities poses a challenge, and solutions are often limited to projections or to rotated views of the 3D stacks. Here, we present SparStVR, a virtual reality application for interactive 3D image data visualization. A virtual environment with textured 3D models and, when desired, embedded measurements is generated from a stack of labeled masks and stacks of color images. In addition, modeling whole sample from sample masks and embedding multimodal measurements from heatmaps are supported. The possibility to interactively and intuitively study 3D structures and measurements in virtual reality is a ground-breaking feature compared to traditional tools. SparStVR was designed especially for visualization of sparse 3D histology data, yet it can be used for any 3D image data with objects of interest to model. SparStVR enables discoveries from complex data of tissue structures and pathology in an unprecedented manner.

Identifiers

PMID41820598
PMCPMC13125238

What OpenQuestion holds

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Registered trials

None linked

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.