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Fantham M, Kaminski CF, "First Person Bioimage: An Online Tool for Presentation and Publication of Volumetric Data"Biophys. J. (2017), 112(3), 583a.

DOI: 10.1016/j.bpj.2016.11.3139 | pdf


Abstract

New microscopy techniques (e.g. SPIM, 3D STORM, OPT, etc.) and many other 3D bioimaging modalities (tomographic EM, MRI, CT, etc.) generate terabytes of volumetric data. Whilst highly specialized software packages are available for the analysis and visualization of such data, their use requires specialized skills and they are often costly. Furthermore the capacity to share data and allow interactive exploration by third parties is highly limited.

Here we present FP BioImage, an easy-to-use and powerful open source visualization tool that permits researchers to share their volumetric image data online and third parties to interact with, and explore, datasets in their entirety. FP BioImage provides the viewer an immersive experience for the exploration of complex 3-dimensional bioimaging data, and makes use of the latest graphics capabilities embedded in all modern web browsers so that no software installation is required.

The tool is fast and user responsive, requires no training for use, and includes advanced rendering and data manipulation capabilities. Data can be intuitively explored from a ‘first person perspective’, akin to navigating virtual space in modern computer games, allowing users to conceptualize and contextualize details in the data to aid biological interpretation.

From a researcher's perspective the tool makes it now possible to easily share volumetric imaging data globally, providing anyone full and interactive access to the data via a web browser. An example website has been set up at http://fpb.ceb.cam.ac.uk. In the future, we hope that this changes the way research data are shared and suggest that publishers will use the software for online publication. Data can thus be shared in their entirety, moving on from the current practice of providing selective views or movies shown from a single perspective, which are not capable of providing a full understanding of the data.

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