Statistical segmentation and porosity quantification of 3D x-ray microtomography
Statistical segmentation and porosity quantification of 3D x-ray microtomography
复制标题
3D X 射线显微断层扫描的统计分割和孔隙度量化
DOI：
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发表时间：
2011
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通讯作者：
J. Sethian
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作者：
D. Ushizima;D. Parkinson;P. Nico;J. Ajo;A. MacDowell;B. Kocar;W. Bethel;J. Sethian
高分辨率X射线显微层析成像用于在3D中以微米尺度对固体材料进行成像。我们的目标是实施无损技术来量化固体物体内部的属性，包括它们的3D几何形状的信息，这支持将流体动力学建模到宿主物体的孔隙空间中。微断层摄影数据采集过程生成大数据集，当使用当前标准计算和图像处理算法时，这些大数据集通常难以以足够的性能处理。我们提出了一套有效的算法来过滤，分割和提取的多孔介质的图像切片堆栈的功能。第一步调整滤波算法的尺度参数，然后使用应用于图像堆栈的快速各向异性滤波器来减少伪影，该滤波器在保持边界的同时平滑均匀区域。接下来，使用统计区域合并来划分体积，利用每个片段的强度相似性。最后，我们根据固体孔隙比计算材料的孔隙率。我们的贡献是设计一个管道量身定制，以处理大型数据文件，包括一个计划，为用户输入图像补丁调整参数的数据集。我们说明了我们的方法，使用超过2,000微断层扫描图像切片从4种不同的多孔材料，使用高分辨率X射线采集。此外，我们比较我们的结果与标准的，但快速算法通常用于图像分割，其中包括中值滤波和阈值。
High-resolution x-ray micro-tomography is used for imaging of solid materials at micrometer scale in 3D. Our goal is to implement nondestructive techniques to quantify properties in the interior of solid objects, including information on their 3D geometries, which supports modeling of the fluid dynamics into the pore space of the host object. The micro-tomography data acquisition process generates large data sets that are often difficult to handle with adequate performance when using current standard computing and image processing algorithms. We propose an efficient set of algorithms to filter, segment and extract features from stacks of image slices of porous media. The first step tunes scale parameters to the filtering algorithm, then it reduces artifacts using a fast anisotropic filter applied to the image stack, which smoothes homogeneous regions while preserving borders. Next, the volume is partitioned using statistical region merging, exploiting the intensity similarities of each segment. Finally, we calculate the porosity of the material based on the solid-void ratio. Our contribution is to design a pipeline tailored to deal with large data-files, including a scheme for the user to input image patches for tuning parameters to the datasets. We illustrate our methodology using more than 2,000 micro-tomography image slices from 4 different porous materials, acquired using high-resolution X-ray. Also, we compare our results with standard, yet fast algorithms often used for image segmentation, which includes median filtering and thresholding.