使用隐马尔可夫测度场模型对心脏CT扫描中的肺气肿进行量化：多民族动脉粥样硬化研究（MESA Lung Study）
Emphysema Quantification on Cardiac CT Scans Using Hidden Markov Measure Field Model: The MESA Lung Study.
作者信息
Yang Jie, Angelini Elsa D, Balte Pallavi P, Hoffman Eric A, Wu Colin O, Venkatesh Bharath A, Barr R Graham, Laine Andrew F
机构信息
Department of Biomedical Engineering, Columbia University, New York, NY, USA.
Department of Medicine, Columbia University Medical Center, New York, NY, USA.
出版信息
Med Image Comput Comput Assist Interv. 2016 Oct;9901:624-631. doi: 10.1007/978-3-319-46723-8_72. Epub 2016 Oct 2.
Abstract
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.
摘要
心脏计算机断层扫描（CT）可覆盖约2/3的肺部，且辐射剂量低。大量基于人群的研究报告称，使用基于阈值的测量方法，全肺（FL）CT扫描和心脏CT扫描在肺气肿定量方面具有高度相关性。这项工作扩展了基于隐马尔可夫测度场（HMMF）模型的分割方法，用于在心脏CT扫描上自动进行肺气肿定量分析。我们表明，与几种阈值法相比，基于HMMF的方法在重复心脏扫描时能提供更可重复的肺气肿分割，并且在来自不同类型扫描仪的数千名受试者的上万次扫描中，纵向心脏扫描和FL扫描之间的测量结果更一致。
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