Denoising and multivariate analysis of time-of-flight SIMS images
Denoising and multivariate analysis of time-of-flight SIMS images
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DOI：
10.1002/sia.1580
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发表时间：
2003-08-01
影响因子：
1.7
通讯作者：
Castner, DG
中科院分区：
文献类型：
--
作者：
Wickes, BT;Kim, Y;Castner, DG
飞行时间 SIMS (ToF-SIMS) 成像提供了一种同时可视化不同表面物种空间分布的模式。然而，ToF-SIMS 数据集的实用性可能会受到其大尺寸、质量分辨率下降和每像素离子计数低的限制。通过去噪和多变量图像分析，可以更容易地区分 ToF-SIMS 图像数据中具有相似化学成分的区域。三种已建立的去噪算法——下分箱、箱车和小波滤波——被应用于不同表面几何形状和化学成分的 ToF-SIMS 图像。这些滤波器对主成分分析 (PCA) 性能的影响是根据主成分得分图像中重要化学图像特征的捕获、主成分得分图像的质量以及主成分解释负责图像对比度的化学物质的能力来评估的。通过改进图像特征的捕获并生成比未过滤的离子图像质量更高的主成分评分图像，发现所有过滤方法都可以提高所研究的所有图像数据集的 PCA 性能。过滤和未过滤 PCA 模型的载荷通过识别定义不同表面化学区域的峰来描述化学对比区域。对图像进行下装以增加像素大小和信号是提高 PCA 性能的最有效技术。版权所有 (C) 2003 John Wiley Sons, Ltd.
Time-of-flight SIMS (ToF-SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF-SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF-SIMS image data. Three established denoising algorithms-down-binning, boxcar and wavelet filtering-were applied to ToF-SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component score images and the ability of the principal components to explain the chemistries responsible for the image contrast. All filtering methods were found to improve the performance of PCA for all image datasets studied by improving capture of image features and producing principal component score images of higher quality than the unfiltered ion images. The loadings for filtered and unfiltered PCA models described the regions of chemical contrast by identifying peaks defining the regions of different surface chemistry. Down-binning the images to increase pixel size and signal was the most effective technique to improve PCA performance. Copyright (C) 2003 John Wiley Sons, Ltd.