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Fiberweb: Diffusion Visualization and Processing in the Browser

机译:Fiberweb:浏览器中的扩散可视化和处理

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Data visualization is one of the most important tool to explore the brain as we know it. In this work, we introduce a novel browser-based solution for medical imaging data visualization and interaction with diffusion-weighted magnetic resonance imaging (dMRI) and tractography data: Fiberweb. It uses a recent technology, WebGL, that has yet to be fully explored for medical imaging purposes. There are currently very few software tools that allow medical imaging data visualization in the browser, and none of these tools support efficient data interaction and processing, such as streamlines selection and real-time deterministic and probabilistic tractography (RTT). With Fiberweb allowing these types of interaction, it is no longer the case. We show results of the visualization of medical imaging data, and demonstrate that our new RTT probabilistic algorithm can compare to a state of the art offline algorithm. Overall, Fiberweb pushes the boundary of interaction combined with scientific visualization, which opens great perspectives for quality control and neurosurgical navigation on browser-based mobile and static devices.
机译:众所周知,数据可视化是探索大脑的最重要工具之一。在这项工作中,我们介绍了一种基于浏览器的新颖解决方案,用于医学成像数据可视化以及与扩散加权磁共振成像(dMRI)和体检数据的交互:Fiberweb。它使用了最新技术WebGL,但尚未完全开发用于医学成像目的。当前,几乎没有允许在浏览器中显示医学影像数据的软件工具,并且这些工具都不支持有效的数据交互和处理,例如流线型选择以及实时确定性和概率性眼底成像(RTT)。通过Fiberweb允许这些类型的交互,情况已不再如此。我们展示了医学成像数据的可视化结果,并证明了我们的新RTT概率算法可以与最先进的离线算法进行比较。总体而言,Fiberweb突破了结合科学可视化的界限,为基于浏览器的移动和静态设备上的质量控制和神经外科导航打开了广阔的前景。

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