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首页> 外文会议>Visualization, Image-Guided Procedures pt.2; Progress in Biomedical Optics and Imaging; vol.8 no.28; Proceedings of SPIE-The International Society for Optical Engineering; vol.6509 pt.2 >Efficient Hardware Accelerated Rendering of Multiple Volumes by Data Dependent Local Render Functions
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Efficient Hardware Accelerated Rendering of Multiple Volumes by Data Dependent Local Render Functions

机译：通过依赖数据的本地渲染功能，高效地硬件加速多个体积的渲染

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摘要

The inspection of a patient's data for diagnostics, therapy planning or therapy guidance involves an increasing number of 3D data sets, e.g. acquired by different imaging modalities, with different scanner settings or at different times. To enable viewing of the data in one consistent anatomical context fused interactive renderings of multiple 3D data sets are desirable. However, interactive fused rendering of typical medical data sets using standard computing hardware remains a challenge. In this paper we present a method to render multiple 3D data sets. By introducing local rendering functions, i.e. functions that are adapted to the complexity of the visible data contained in the different regions of a scene, we can ensure that the overall performance for fused rendering of multiple data sets depends on the actual amount of visible data. This is in contrast to other approaches where the performance depends mainly on the number of rendered data sets. We integrate the method into a streaming rendering architecture with brick-based data representations of the volume data. This enables efficient handling of data sets that do not fit into the graphics board memory and a good utilization of the texture caches. Furthermore, transfer and rendering of volume data that does not contribute to the final image can be avoided. We illustrate the benefits of our method by experiments with clinical data.
机译：检查患者数据以进行诊断，治疗计划或治疗指导涉及越来越多的3D数据集，例如通过不同的成像方式，不同的扫描仪设置或在不同的时间获取。为了能够在一个一致的解剖学上下文中查看数据，需要多个3D数据集的融合交互式渲染。然而，使用标准计算硬件对典型医学数据集进行交互式融合渲染仍然是一个挑战。在本文中，我们提出了一种渲染多个3D数据集的方法。通过引入局部渲染功能，即适合于场景不同区域中包含的可见数据复杂性的功能，我们可以确保融合渲染多个数据集的整体性能取决于可见数据的实际数量。这与其他方法相反，在其他方法中，性能主要取决于渲染数据集的数量。我们将该方法集成到具有基于块数据的体数据表示形式的流呈现架构中。这样可以有效地处理不适合图形卡内存的数据集，并可以很好地利用纹理缓存。此外，可以避免对最终图像没有贡献的体数据的传输和渲染。我们通过临床数据实验说明了我们方法的好处。

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