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Interactive Exploration of Large Remote Micro-CT Scans

机译:大型远程Micro-CT扫描的互动探索

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Datasets of tens of gigabytes are becoming common in computational and experimental science. This development is driven by advances in imaging technology, producing detectors with growing resolutions, as well as availability of cheap processing power and memory capacity in commodity-based computing clusters. In this article we describe the design of a visualization system that allows scientists to interactively explore large remote data sets in an efficient and flexible way. The system is broadly applicable and currently used by medical scientists conducting an osteoporosis research project. Human vertebral bodies are scanned using a high resolution micro-CT scanner producing scans of roughly 8 GB size each. All participating research groups require access to the centrally stored data. Due to the rich internal bone structure, scientists need to interactively explore the full dataset at coarse levels, as well as visualize subvolumes of interest at the highest resolution. Our solution is based on HDF5 and GridFTP. When accessing data remotely, the HDF5 data processing pipeline is modified to support efficient retrieval of subvolumes. We reduce the overall latency and optimize throughput by executing high-level operations on the remote side. The GridFTP protocol is used to pass the HDF5 requests to a customized server. The approach takes full advantage of local graphics hardware for rendering. Interactive visualization is accomplished using a background thread to access the datasets stored in a multi-resolution format. A hierarchical volume renderer provides seamless integration of high resolution details with low resolution overviews.
机译:数十GB的数据集在计算和实验科学中变得越来越普遍。这种发展是由成像技术的进步所推动的,该技术产生了分辨率不断提高的检测器,以及基于商品的计算集群中廉价的处理能力和存储容量的可用性。在本文中,我们描述了可视化系统的设计,该系统允许科学家以有效且灵活的方式交互式地探索大型远程数据集。该系统广泛适用,目前正由进行骨质疏松症研究项目的医学科学家使用。使用高分辨率微型CT扫描仪扫描人体椎骨,每次扫描约8 GB。所有参与研究的小组都需要访问集中存储的数据。由于内部骨骼结构丰富,科学家需要在粗糙级别上交互式地探索整个数据集,并以最高分辨率可视化感兴趣的子体积。我们的解决方案基于HDF5和GridFTP。远程访问数据时,对HDF5数据处理管道进行了修改,以支持子卷的有效检索。通过在远程端执行高级操作,我们减少了总体延迟并优化了吞吐量。 GridFTP协议用于将HDF5请求传递到自定义服务器。该方法充分利用了本地图形硬件进行渲染。使用后台线程访问以多分辨率格式存储的数据集可以实现交互式可视化。分层体积渲染器提供了高分辨率细节与低分辨率概览的无缝集成。

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