Quantification of pulmonary emphysema from lung computed tomography images
Quantification of pulmonary emphysema from lung computed tomography images
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DOI：
10.1164/ajrccm.156.1.9606093
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发表时间：
1997-07-01
影响因子：
24.7
通讯作者：
McLennan, G
中科院分区：
文献类型：
--
作者：
Uppaluri, R;Mitsa, T;McLennan, G
描述了一种基于纹理的自适应多特征方法(AMFM)，用于从CT图像中评估肺实质。该方法融合了多种统计和分形纹理特征。AMFM与之前发表的两种方法进行了比较，即平均肺密度(MLD)和直方图最低五百分位数(HIST)。首先，研究了这些方法检测俯卧位正常肺阶梯腹侧-背侧肺密度梯度细微差异的能力。比较两种方法对正常肺切片和肺气肿全肺切片的区分能力，最后对正常肺和肺气肿肺进行区域分析，将CT切片上的肺分为腹侧和背侧6个相等的区域，并分别对各区域进行分析。结果表明，AMFM可以区分正常俯卧肺的腹侧和背侧1/3，准确率为89.8%，而MLD和HIST方法的准确率分别为74.6%和64.4%。与MLD和HIST方法分别为94.7%和97.4%的准确率相比，AMFM在全球范围内对正常和肺气肿切片的分离准确率为100.0%。AMFM、MLD和HIST方法对区域正常组织和肺气肿组织的平均判别准确率分别为97.9%、89.9%和99.1%。正常组和肺气肿组的肺功能与三种方法的相关性较差。使用自适应多特征的定量纹理分析有望对肺实质进行客观的非侵入性评估。
A texture-based adaptive multiple feature method (AMFM) for evaluating pulmonary parenchyma from computed tomography (CT) images is described. This method incorporates multiple statistical and fractal texture features. The AMFM was compared to two previously published methods, namely, mean lung density (MLD) and the lowest fifth percentile of the histogram (HIST). First, the ability of these methods to detect subtle differences in ventral-dorsal lung density gradient in the prone normal rung was studied. Second, their abilities to differentiate between normal and emphysematous whole lung slices were compared, Finally, regional analyses comparing normal and emphysematous regions were performed by dividing the lungs in the CT slices into six equal regions, ventral to dorsal, and analyzing each region separately, The results demonstrated that the AMFM could separate the ventral from the dorsal one-third of the normal prone lung with 89.8% accuracy, compared to an accuracy of 74.6% with the MLD and 64.4% with the HIST methods. The normal and emphysematous slices were separated on a global basis with 100.0% accuracy using the AMFM as compared to an accuracy of 94.7% and 97.4% using the MLD and HIST methods, respectively. The regional normal and emphysematous tissues were discriminated with an average accuracy of 97.9%, 89.9%, and 99.1% with the AMFM, MLD, and HIST methods, respectively. The three methods and the pulmonary function tests in the normal and emphysema groups were poorly correlated. Quantitative texture analysis using adaptive multiple features holds promise for the objective noninvasive evaluation of the pulmonary parenchyma.