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Automatic Marching Cubes for Improving 3D Medical Images Reconstruction

机译:自动行进多维数据集可改善3D医学图像重建

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The Marching Cubes algorithm is based on the estimate of the isovalue in order to determine all the pixels that are belonging to the volume to be reconstructed. This estimation is done by the user in an interactive and way without any orientation; this is no longer an intuitive process. Solutions are proposed to detect more than one isovalue and have been used to display multiple isosurfaces and not to adjust or automatically determine isovalue. Other solutions propose to explore histogram to estimate isovalue automatically; those remain insufficient because they still require user intervention. The proposed method acts directly in the isovalue estimation phase. In fact, we propose to make this estimate by using automatic methods of sampling, which have shown their performance in estimating a threshold in several works. This paper proposes to make the use of existing automated isovalue selection methods that take into account histogram and the dynamics of the image. The automatic Marching Cubes algorithm reduces user interaction and makes the selection process more intuitive. The obtained results will show that this adaptation minimizes the computing time and that the obtained volumes are of better quality than those obtained by the classical Marching Cubes algorithm.
机译:Marching Cubes算法基于等值估计,以确定属于要重建的体积的所有像素。该估计由用户以交互方式进行,没有任何方向;这不再是一个直观的过程。提出了用于检测多个等值的解决方案,并且已将其用于显示多个等值面,而不用于调整或自动确定等值。其他解决方案建议探索直方图以自动估计等值。这些仍然不足,因为它们仍需要用户干预。所提出的方法直接作用于等值估计阶段。实际上,我们建议使用自动采样方法进行此估算,这些方法已显示出其在多项工作中估算阈值的性能。本文建议利用现有的自动等值选择方法,该方法考虑了直方图和图像的动力学。自动Marching Cubes算法减少了用户交互,并使选择过程更加直观。所获得的结果将表明,这种适应可最大程度地减少计算时间,并且所获得的体积比经典的Marching Cubes算法所获得的体积质量更好。

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