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WYSIWYP: What You See Is What You Pick

机译:所见即所得:所见即所得

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摘要

Scientists, engineers and physicians are used to analyze 3D data with slice-based visualizations. Radiologists for example are trained to read slices of medical imaging data. Despite the numerous examples of sophisticated 3D rendering techniques, domain experts, who still prefer slice-based visualization do not consider these to be very useful. Since 3D renderings have the advantage of providing an overview at a glance, while 2D depictions better serve detailed analyses, it is of general interest to better combine these methods. Recently there have been attempts to bridge this gap between 2D and 3D renderings. These attempts include specialized techniques for volume picking in medical imaging data that result in repositioning slices. In this paper, we present a new volume picking technique called WYSIWYP ("what you see is what you pick") that, in contrast to previous work, does not require pre-segmented data or metadata and thus is more generally applicable. The positions picked by our method are solely based on the data itself, the transfer function, and the way the volumetric rendering is perceived by the user. To demonstrate the utility of the proposed method, we apply it to automated positioning of slices in volumetric scalar fields from various application areas. Finally, we present results of a user study in which 3D locations selected by users are compared to those resulting from WYSIWYP. The user study confirms our claim that the resulting positions correlate well with those perceived by the user
机译:科学家,工程师和医师被用来通过基于切片的可视化来分析3D数据。例如,放射科医生受过训练,可以读取医学成像数据的切片。尽管有许多复杂的3D渲染技术的示例,但是仍然偏爱基于切片的可视化的领域专家并不认为它们非常有用。由于3D渲染的优点是可以一目了然地提供概览,而2D描绘可以更好地为详细分析提供服务,因此更好地结合使用这些方法通常是令人感兴趣的。最近,人们尝试弥合2D和3D渲染之间的差距。这些尝试包括用于在医学成像数据中进行体积拾取的专业技术,这些技术会导致切片重新定位。在本文中,我们提出了一种称为WYSIWYP(“所见即所得”)的新的批量选择技术,与以前的工作相比,该技术不需要预先分段的数据或元数据,因此更普遍地适用。我们的方法选择的位置仅基于数据本身,传递函数以及用户感知体积渲染的方式。为了演示该方法的实用性,我们将其应用于来自各个应用领域的体积标量字段中的切片自动定位。最后,我们介绍了一项用户研究的结果,其中将用户选择的3D位置与“所见即所得”所得到的位置进行了比较。用户研究证实了我们的主张,即所得到的位置与用户所感知的位置很好地相关

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