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体素可见性模型:一种用于传递函数设计的高效框架。

The voxel visibility model: an efficient framework for transfer function design.

作者信息

Qin Hongxing, Ye Bin, He Rui

机构信息

Chongqing Key Laboratory of Computational Intelligence, Chongqing 400065, China; College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

Chongqing Key Laboratory of Computational Intelligence, Chongqing 400065, China; College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

出版信息

Comput Med Imaging Graph. 2015 Mar;40:138-46. doi: 10.1016/j.compmedimag.2014.11.014. Epub 2014 Dec 2.

Abstract

Volume visualization is a very important work in medical imaging and surgery plan. However, determining an ideal transfer function is still a challenging task because of the lack of measurable metrics for quality of volume visualization. In the paper, we presented the voxel vibility model as a quality metric to design the desired visibility for voxels instead of designing transfer functions directly. Transfer functions are obtained by minimizing the distance between the desired visibility distribution and the actual visibility distribution. The voxel model is a mapping function from the feature attributes of voxels to the visibility of voxels. To consider between-class information and with-class information simultaneously, the voxel visibility model is described as a Gaussian mixture model. To highlight the important features, the matched result can be obtained by changing the parameters in the voxel visibility model through a simple and effective interface. Simultaneously, we also proposed an algorithm for transfer functions optimization. The effectiveness of this method is demonstrated through experimental results on several volumetric data sets.

摘要

体数据可视化是医学成像和手术规划中一项非常重要的工作。然而,由于缺乏用于评估体数据可视化质量的可测量指标,确定理想的传递函数仍然是一项具有挑战性的任务。在本文中,我们提出了体素可见性模型作为一种质量度量,用于设计体素的期望可见性,而不是直接设计传递函数。通过最小化期望可见性分布与实际可见性分布之间的距离来获得传递函数。体素模型是一个从体素的特征属性到体素可见性的映射函数。为了同时考虑类间信息和类内信息,体素可见性模型被描述为高斯混合模型。为了突出重要特征,可以通过一个简单有效的接口改变体素可见性模型中的参数来获得匹配结果。同时,我们还提出了一种传递函数优化算法。通过在几个体数据集上的实验结果证明了该方法的有效性。

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