Casting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation times. Here, a casting method using contrast-enhanced diethylphthalate (DEP) for μCT of snow is presented. The X-ray contrast of DEP is enhanced with barium titanate nanoparticles (BaTiO3) and iodine (I2). A partially unsupervised, three-phase segmentation method utilizing traditional Gaussian smoothing followed by a three-step process to address transition voxels is also presented. Synthetic images derived from real snow samples are used to evaluate the segmentation method with various configurations of trapped air bubbles. Real snow samples spanning a range of specific surface areas (SSAs) (8–28 m2 kg−1) and densities (135–463 kg m−3) are used to assess the performance of the segmentation method on real, cast samples. The method yields SSA, density and correlation length errors of less than 10% for synthetic images with air bubble surface areas less than 333 m−1 per sample volume for eight of the nine snow samples. For eight of the nine cast samples, the method yields errors of less than 10% for all three parameters.

中文翻译：

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一种使用对比增强邻苯二甲酸二乙酯的铸造方法用于雪的微型计算机断层扫描

在 X 射线微计算机断层扫描 (μCT) 成像之前，必须浇铸雪以防止变质和变形。由于与铸造介质相关的安全考虑和/或冗长的样品制备时间，目前的方法不足以对雪进行大规模现场采样。本文介绍了一种使用对比度增强的邻苯二甲酸二乙酯 (DEP) 对雪的 μCT 进行铸造的方法。钛酸钡纳米粒子（BaTiO2）增强了 DEP 的 X 射线对比度3) 和碘 (一世2）。还提出了一种部分无监督的三相分割方法，该方法利用传统的高斯平滑，然后是三步过程来解决过渡体素。来自真实雪样的合成图像用于评估具有各种捕获气泡配置的分割方法。跨越一系列比表面积 (SSA) (8–28 m) 的真实雪样2公斤-1) 和密度 (135–463 kg m-3) 用于评估分割方法在真实铸造样本上的性能。对于气泡表面积小于 333 m 的合成图像，该方法产生的 SSA、密度和相关长度误差小于 10%-1九个雪样中的八个的每个样本体积。对于九个铸造样品中的八个，该方法对所有三个参数产生的误差都小于 10%。