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Visualization of boundaries in CT volumetric data sets using dynamic M - vertical bar del f vertical bar histogram

机译:使用动态M-垂直条形图和垂直条形图直方图可视化CT体积数据集中的边界

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摘要

Direct volume rendering is widely used for three-dimensional medical data visualization such as computed tomography and magnetic resonance imaging. Distinct visualization of boundaries is able to provide valuable and insightful information in many medical applications. However, it is conventionally challenging to detect boundaries reliably due to limitations of the transfer function design. Meanwhile, the interactive strategy is complicated for new users or even experts. In this paper, we build a generalized boundary model contaminated by noise and prove boundary middle value (M) has a good statistical property. Based on the model we propose a user-friendly strategy for the boundary extraction and transfer function design, using M, boundary height (Delta h), and gradient magnitude (vertical bar del f vertical bar). In fact, it is a dynamic iterative process. First, potential boundaries are sorted orderly from high to low according to the value of their height. Then, users iteratively extract the boundary with the highest value of Delta h in a newly defined domain, where different boundaries are transformed to disjoint vertical bars using M-vertical bar del f vertical bar histogram. In this case, the chance of misclassification among different boundaries decreases. (C) 2015 Elsevier Ltd. All rights reserved.
机译:直接体绘制被广泛用于三维医学数据可视化,例如计算机断层扫描和磁共振成像。边界的清晰可视化能够在许多医疗应用中提供有价值的信息。然而,由于传递函数设计的限制,传统上难以可靠地检测边界。同时,对于新用户甚至专家而言,交互式策略都很复杂。本文建立了一个被噪声污染的广义边界模型,证明边界中间值(M)具有良好的统计特性。基于该模型,我们为边界提取和传递函数设计提出了一种用户友好的策略,该策略使用M,边界高度(Delta h)和梯度幅度(vertical bar del f垂直bar)。实际上,这是一个动态的迭代过程。首先,根据边界的高度值,将其从高到低排序。然后,用户在新定义的域中迭代提取Δh值最高的边界,其中使用M-vertical bar delf垂直条形直方图将不同边界转换为不相交的垂直条形。在这种情况下,不同边界之间错误分类的机会会减少。 (C)2015 Elsevier Ltd.保留所有权利。

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