Yang Jie, Angelini Elsa D, Balte Pallavi P, Hoffman Eric A, Wu Colin O, Venkatesh Bharath A, Barr R Graham, Laine Andrew F
Department of Biomedical Engineering, Columbia University, New York, NY, USA.
Department of Medicine, Columbia University Medical Center, New York, NY, USA.
Med Image Comput Comput Assist Interv. 2016 Oct;9901:624-631. doi: 10.1007/978-3-319-46723-8_72. Epub 2016 Oct 2.
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.
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。
