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Fast Maximum Intensity Projection with 3D Non-Linear Wavelets

机译:利用3D非线性小波快速进行最大强度投影

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Despite the increasing interest in three-dimensional (3D) visualization, rendering algorithms still suffer from high numerical complexity and large memory requirements. With the continuously increasing volume of medial imaging data, fast visualization algorithms become crucial. Powerful mathematical techniques based on the wavelet transform promise to provide efficient multi-resolution visualization algorithms, optimizing hence 3D rendering. Maximum Intensity Projection (MIP) is a 3D rendering algorithm that is used to visualize high-intensity structures within volumetric data. At each pixel the highest data value, which is encountered along a corresponding viewing ray, is depicted. In this paper, we propose a fast MIP 3D rendering that is based on a new hierarchical data representation. The proposed approach uses on a new morphological wavelet decomposition that allows for fast initial rendering and progressive subsequent refinements. Our method includes a pre-processing step that is based on a non-linear wavelet representation in order to achieve efficient data compression and storage. It results in a very fast visualization algorithm. The rendering speed-up results from removing cells that do not contribute to any MIP projection and from an innovative storage scheme of the volume cells. The proposed algorithm gives very promising results. Very good MIP projections can be obtained with less than 20% of the volumetric data. This makes our algorithm very competitive with the best MIP methods proposed so far in the literature.
机译:尽管对三维(3D)可视化的兴趣日益浓厚,但是渲染算法仍然遭受着很高的数值复杂性和大内存需求。随着内侧成像数据量的不断增加,快速的可视化算法变得至关重要。基于小波变换的强大数学技术有望提供有效的多分辨率可视化算法,从而优化3D渲染。最大强度投影(MIP)是一种3D渲染算法,用于可视化体积数据中的高强度结构。在每个像素处,描绘了沿着相应的视线遇到的最高数据值。在本文中,我们提出了一种基于新的分层数据表示的快速MIP 3D渲染。提出的方法使用了一种新的形态学小波分解,可以快速进行初始渲染并逐步进行后续细化。我们的方法包括一个基于非线性小波表示的预处理步骤,以实现高效的数据压缩和存储。这导致非常快速的可视化算法。渲染速度的提高是由于删除了不会对任何MIP投影起作用的单元以及体积单元的创新存储方案。所提出的算法给出了非常有希望的结果。少于20%的体积数据可以获得非常好的MIP投影。这使得我们的算法与迄今为止文献中提出的最佳MIP方法相比具有很大的竞争力。

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