在三维显微层析图像中选择质量最高的区域

A. Kornilov, I. Safonov, A. V. Goncharova, I. Yakimchuk
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引用次数: 1

摘要

我们提出了一种处理x射线显微断层成像(micro-CT)图像的算法,该算法允许自动选择具有最佳视觉质量的子体积进行进一步的数学模拟,例如,流动模拟。通常,被调查的样品只占体积图像的一部分,或者样品可以放入容器中;可以裁剪图像的一部分。对于图像z轴上的每个二维切片,该方法定位一个与样本对应的区域。我们探索了几种现有的盲质量措施的应用,以估计微ct图像切片的视觉质量。其中一些指标可以根据图像区域的质量对其进行排序。我们的方法搜索位于属于样本的区域内部的立方体区域,并提供沿z轴穿过立方体的切片的质量度量的最大总和。在岩石的合成微ct图像和真实微ct图像上进行了测试。
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Selection in a 3D microtomographic image the region with the highest quality
We present an algorithm for processing of X-ray microtomographic (micro-CT) images that allows automatic selection of a sub-volume having the best visual quality for further mathematical simulation, for example, flow simulation. Frequently, an investigated sample occupies only a part of a volumetric image or the sample can be into a holder; a part of the image can be cropped. For each 2D slice across the Z-axis of an image, the proposed method locates a region corresponding to the sample. We explored applications of several existing blind quality measures for an estimation of the visual quality of a micro-CT image slice. Some of these metrics can be applied to ranking the image regions according to their quality. Our method searches for a cubic area located inside regions belonging to the sample and providing the maximal sum of the quality measures of slices crossing the cube across the Z-axis. The proposed technique was tested on synthetic and real micro-CT images of rocks.
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