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Diva images
Diva images







diva images

Through the seamless integration of stereoscopy, motion tracking and total immersion, VR provides a natural means to visualize 3D structures. Recently, virtual reality (VR) has reemerged as a technology of interest in a host of applications due in large part to new low-cost consumer headsets. clicking 10 inside a 3D object on a 2D screen is a nontrivial task. Namely, viewing 3D data on a computer monitor while simultaneously using a mouse to interact and extract information is tedious and difficult, e.g. Yet, gaining an intuitive understanding from these complex raw data remains a challenge, as natural modes of 3D visualization are lacking.

diva images

Entire organisms can be imaged at sub-cellular resolution and the complex interplay between 3D geometry and biological activity explored. Technological advances in the fields of optical and electron microscopy (EM) have enhanced our abilities to discern three-dimensional (3D) biological structures via slice-based tomography.

diva images

DIVA is available at and will be regularly updated. We benchmark the software with diverse image types including those generated by confocal, light-sheet and electron microscopy.

diva images

In contrast to similar solutions, our software provides high-quality volume rendering with native TIFF file compatibility. In DIVA's immersive virtual environment, users can view, manipulate and perform volumetric measurements on their microscopy images as they would to real physical objects. With this motivation, we present DIVA, a user-friendly software tool that automatically creates detailed three-dimensional reconstructions of raw experimental image stacks that are integrated in virtual reality. Through stereoscopy and motion tracking, commercial virtual reality headsets provide a solution to this important visualization challenge by allowing researchers to view volumetric objects in an entirely intuitive fashion. As three-dimensional microscopy becomes commonplace in biological research, there is an increasing need for researchers to be able to view experimental image stacks in a natural three-dimensional viewing context.









Diva images