Modern high-throughput bioimaging techniques pose the unprecedented challenge of exploring and analyzing the produced Terabyte-scale volumetric images directly in their 3D space. Without expensive virtual reality devices and/or parallel computing infrastructures, this becomes even more demanding and calls for new, more scalable tools that help exploring these very large 3D data also on common laptops and graphic hardware. To this end, we developed a plugin for the open-source, cross-platform Vaa3D system to extend its powerful 3D visualization and analysis capabilities to images of potentially unlimited size. When used with large volumetric images up to 2.5 Terabyte in size, Vaa3D-TeraFly exhibited real-time (subsecond) performance that scaled constantly on image size. The tool has been implemented in C++ with Qt and OpenGL and it is freely and publicly available both as open-source and as binary package along with the main Vaa3D distribution.

An open-source VAA3D plugin for real-time 3D visualization of terabyte-sized volumetric images

Bria, Alessandro
;
2015-01-01

Abstract

Modern high-throughput bioimaging techniques pose the unprecedented challenge of exploring and analyzing the produced Terabyte-scale volumetric images directly in their 3D space. Without expensive virtual reality devices and/or parallel computing infrastructures, this becomes even more demanding and calls for new, more scalable tools that help exploring these very large 3D data also on common laptops and graphic hardware. To this end, we developed a plugin for the open-source, cross-platform Vaa3D system to extend its powerful 3D visualization and analysis capabilities to images of potentially unlimited size. When used with large volumetric images up to 2.5 Terabyte in size, Vaa3D-TeraFly exhibited real-time (subsecond) performance that scaled constantly on image size. The tool has been implemented in C++ with Qt and OpenGL and it is freely and publicly available both as open-source and as binary package along with the main Vaa3D distribution.
2015
978-1-4799-2374-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/67824
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