Combined focused ion beam and scanning electron microscope (FIB‐SEM) tomography is a well‐established technique for high resolution imaging and reconstruction of the microstructure of a wide range of materials. Segmentation of FIB‐SEM data is complicated due to a number of factors; the most prominent is that for porous materials, the scanning electron microscope image slices contain information not only from the planar cross‐section of the material but also from underlying, exposed subsurface pores. In this work, we develop a segmentation method for FIB‐SEM data from ethyl cellulose porous films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. These materials are used for coating pharmaceutical oral dosage forms (tablets or pellets) to control drug release. We study three samples of ethyl cellulose and hydroxypropyl cellulose with different volume fractions where the hydroxypropyl cellulose phase has been leached out, resulting in a porous material. The data are segmented using scale‐space features and a random forest classifier. We demonstrate good agreement with manual segmentations. The method enables quantitative characterization and subsequent optimization of material structure for controlled release applications. Although the methodology is demonstrated on porous polymer films, it is applicable to other soft porous materials imaged by FIB‐SEM. We make the data and software used publicly available to facilitate further development of FIB‐SEM segmentation methods.

中文翻译：

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使用随机森林根据 FIB-SEM 纳米断层扫描数据对多孔聚合物薄膜进行三维重建

聚焦离子束和扫描电子显微镜（FIB-SEM）组合断层扫描是一种成熟的技术，可用于高分辨率成像和重建各种材料的微观结构。由于多种因素，FIB-SEM 数据的分割很复杂；最突出的是，对于多孔材料，扫描电子显微镜图像切片不仅包含来自材料平面横截面的信息，还包含来自底层暴露的地下孔隙的信息。在这项工作中，我们开发了一种对由乙基纤维素和羟丙基纤维素 (EC/HPC) 聚合物共混物制成的乙基纤维素多孔膜的 FIB-SEM 数据进行分割的方法。这些材料用于包衣药物口服剂型（片剂或丸剂）以控制药物释放。我们研究了三种不同体积分数的乙基纤维素和羟丙基纤维素样品，其中羟丙基纤维素相已被浸出，形成多孔材料。使用尺度空间特征和随机森林分类器对数据进行分段。我们证明了与手动分割的良好一致性。该方法能够对控释应用的材料结构进行定量表征和后续优化。尽管该方法是在多孔聚合物薄膜上进行验证的，但它也适用于通过 FIB-SEM 成像的其他软质多孔材料。我们公开使用的数据和软件，以促进 FIB-SEM 分割方法的进一步开发。