3 research outputs found

    Visualization and Analysis Tools for Neuronal Tissue

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    The complex nature of neuronal cellular and circuit structure poses challenges for understanding tissue organization. New techniques in electron microscopy allow for large datasets to be acquired from serial sections of neuronal tissue. These techniques reveal all cells in an unbiased fashion, so their segmentation produces complex structures that must be inspected and analyzed. Although several software packages provide 3D representations of these structures, they are limited to monoscopic projection, and are tailored to the visualization of generic 3D data. On the other hand, stereoscopic display has been shown to improve the immersive experience, with significant gains in understanding spatial relationships and identifying important features. To leverage those benefits, we have developed a 3D immersive virtual reality data display system that besides presenting data visually allows augmenting and interacting with them in a form that facilitates human analysis.;To achieve a useful system for neuroscientists, we have developed the BrainTrek system, which is a suite of software applications suited for the organization, rendering, visualization, and modification of neuron model scenes. A middle cost point CAVE system provides high vertex count rendering of an immersive 3D environment. A standard head- and wand-tracking allows movement control and modification of the scene via the on-screen, 3D menu, while a tablet touch screen provides multiple navigation modes and a 2D menu. Graphic optimization provides theoretically limitless volumes to be presented and an on-screen mini-map allows users to quickly orientate themselves. A custom voice note-taking mechanism has been installed, allowing scenes to be described and revisited. Finally, ray-casting support allows numerous analytical features, including 3D distance and volume measurements, computation and presentation of statistics, and point-and-click retrieval and presentation of raw electron microscopy data. The extension of this system to the Unity3D platform provides a low-cost alternative to the CAVE. This allows users to visualize, explore, and annotate 3D cellular data in multiple platforms and modalities, ranging from different operating systems, different hardware platforms (e.g., tablets, PCs, or stereo head-mounted displays), to operating in an online or off-line fashion. Such approach has the potential to not only address visualization and analysis needs of neuroscientists, but also to become a tool for educational purposes, as well as for crowdsourcing upcoming needs for sheer amounts of neuronal data annotation

    Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display

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    Head mounted displays are characterized by relatively low resolution and low dynamic range. These limitations significantly reduce the visual quality of photo-realistic captures on such displays. This thesis presents an interactive view optimized tone mapping technique for viewing large sized high dynamic range panoramas up to 16384 by 8192 on head mounted displays. This technique generates a separate file storing pre-computed view-adjusted mapping function parameters. We define this technique as ToneTexture. The use of a view adjusted tone mapping allows for expansion of the perceived color space available to the end user. This yields an improved visual appearance of both high dynamic range panoramas and low dynamic range panoramas on such displays. Moreover, by providing proper interface to manipulate on ToneTexture, users are allowed to adjust the mapping function as to changing color emphasis. The authors present comparisons of the results produced by ToneTexture technique against widely-used Reinhard tone mapping operator and Filmic tone mapping operator both objectively via a mathematical quality assessment metrics and subjectively through user study. Demonstration systems are available for desktop and head mounted displays such as Oculus Rift and GearVR
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