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European Research Team Launches Open- Source Imaging Software to Aid Cell Function Analysis

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A team of European researchers has developed an open-source software tool intended to make it easier to process bioimaging data in cell and tissue function studies.

The program, dubbed BioImageXD, is a free open-source software package for analyzing, processing, and visualizing multi-dimensional microscopy images. The software is described in detail in a perspective paper that was published in a recent issue of Nature Methods that focused on tools for bioimage informatics.

According to the paper, BioImageXD "enables publication of precise, reproducible, and modifiable workflows" to help biologists analyze complex processes in the cell and tissue imaging domain.

Pasi Kankaanpää, a BioImageXD developer and a co-author on the paper, told BioInform that the team began creating the software ten years ago, when there were no freely available tools that could adequately visualize 4D confocal imaging data or enable its use in quantitative analysis.

Furthermore, "many of the commercial options were also quite limited and extremely expensive," he said.

Kankaanpää, who is also the coordinator of the cell imaging core at the University of Turku's Centre for Biotechnology, said the developers initially began modifying existing open-source tools for use in their projects.

"The project started growing from there, so we got into contact with programmers and IT specialists and started developing a completely new platform with them" that had to meet certain criteria — such as being open source, adjustable, and extendable — which "we thought in general that bio-imaging software should have," he said.

That ten-year development process has resulted in "one of the largest if not the largest program of its kind available," according to Kankaanpää.

According to the paper, BioImageXD currently offers around 220 tools including applications for deconvolution, registration, basic mathematical and logical processing, and six noise-reduction algorithms. It also includes visualization tools for creating volume renderings, surface renderings, and 3D measurements, among other functionalities.

The developers compared BioImageXD to several open-source imaging suites — Yale University's BioImage Suite, the Fiji implementation of ImageJ, Janelia Farm's Vaa3D, and the University of Wisconsin, Madison's VisBio — as well as to commercial software such as Fluoview from Olympus, Volocity from PerkinElmer, ZEN Lite from Zeiss, and the Matlab Image Processing Toolbox from MathWorks.

The developers assessed how well these packages stacked up against BioImageXD for six design criteria: openness, extensiveness, usability, adjustability, applicability, and extendability.

Regarding the commercial packages, "by definition, they cannot fulfill our first criterion of openness; furthermore, their usability, adjustability and especially extendibility are often restricted," the authors noted. BioImageXD compared "favorably" to these packages in terms of the number of features and performance speed, "but the proprietary software may offer more stability and maturity," they said.

The open-source programs, meanwhile, "may be better suited than BioImageXD for some specific applications, such as filament tracing, image annotation, manual manipulation of individual images or processing of bright-field images. However, BioImageXD often compares favorably to them in speed and has more well-integrated features, especially in areas such as 3D visualization, segmentation, and tracking," the developers determined.

BioImageXD "also offers simulation tools and user-friendly support for high-throughput command pipelines, unlike many other open-source platforms," they wrote. Kankaanpää noted that BioImageXD does not require programming or other bioinformatics skills — at least not for basic analysis tasks — which was a key criterion for the development team.

Advanced users can adjust features as necessary for more complex analysis tasks, he noted.

BioImageXD can be used to analyze molecules as they move on cell surfaces and to explore how they bond together. Scientists can also analyze the composition of cell surfaces, study how cancer cells metastasize in a three-dimensional environment, or measure how effectively viruses and targeted drugs enter cells, according to its developers.

It can also be used to create completely new analysis tools, process thousands of images at the same time, and analyze millions of molecules, the authors said.

Kankaanpää told BioInform that BioImageXD has been used by a team of neurosurgeons to study how neural axons grow after surgery. It has also been used in biochemical assays to study the composition of model lipid membranes, as well as to study electron microscopy images of virus particles.

It has also been used in co-localization studies as well as to study how molecules are transported through the cell membrane among other applications.

"It's more limited by your imagination than anything else," he said.

For the next version of the tool, the developers are redesigning the current architecture so that it better supports the currently available features and other planned applications as well as to increase its speed through the addition of multithreading and parallel computing capabilities, Kankaanpää said.

BioImageXD's development was funded by the Academy of Finland through its FinNano research program; the European Union; and Tekes – the Finnish Funding Agency for Technology and Innovation.

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