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Emphysema Quantification on Cardiac CT Scans Using Hidden Markov Measure Field Model: The MESA Lung Study

机译:使用隐马尔可夫测量场模型对心脏CT扫描进行肺气肿量化:MESA肺研究

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摘要

Cardiac computed tomography (CT) scans include approximately 2/3 of the lung and can be obtained with low radiation exposure. Large cohorts of population-based research studies reported high correlations of emphysema quantification between full-lung (FL) and cardiac CT scans, using thresholding-based measurements. This work extends a hidden Markov measure field (HMMF) model-based segmentation method for automated emphysema quantification on cardiac CT scans. We show that the HMMF-based method, when compared with several types of thresholding, provides more reproducible emphysema segmentation on repeated cardiac scans, and more consistent measurements between longitudinal cardiac and FL scans from a diverse pool of scanner types and thousands of subjects with ten thousands of scans.
机译:心脏计算机断层扫描(CT)扫描包括大约2/3的肺部,并且可以在低辐射下获得。大量的基于人群的研究报告表明,使用基于阈值的测量,肺部全肺(FL)扫描和心脏CT扫描之间的肺气肿量化高度相关。这项工作扩展了基于隐马尔可夫测量场(HMMF)模型的分割方法,可用于对心脏CT扫描进行自动气肿量化。我们显示,与几种类型的阈值处理相比,基于HMMF的方法可在重复的心脏扫描中提供更可重复的肺气肿分割,并在来自不同类型的扫描仪库和成千上万的十个受试者的纵向心脏和FL扫描之间提供更一致的测量结果数千次扫描。

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