University of North Carolina (UNC) at Chapel Hill, NC, USA.
Kitware, Inc., Carrboro, NC, USA.
Med Image Anal. 2014 May;18(4):684-98. doi: 10.1016/j.media.2014.03.001. Epub 2014 Mar 29.
Atlas-building from population data is widely used in medical imaging. However, the emphasis of atlas-building approaches is typically to estimate a spatial alignment to compute a mean/median shape or image based on population data. In this work, we focus on the statistical characterization of the population data, once spatial alignment has been achieved. We introduce and propose the use of the weighted functional boxplot. This allows the generalization of concepts such as the median, percentiles, or outliers to spaces where the data objects are functions, shapes, or images, and allows spatio-temporal atlas-building based on kernel regression. In our experiments, we demonstrate the utility of the approach to construct statistical atlases for pediatric upper airways and corpora callosa revealing their growth patterns. We also define a score system based on the pediatric airway atlas to quantitatively measure the severity of subglottic stenosis (SGS) in the airway. This scoring allows the classification of pre- and post-surgery SGS subjects and radiographically normal controls. Experimental results show the utility of atlas information to assess the effect of airway surgery in children.
基于人群数据的图谱构建在医学成像中被广泛应用。然而，图谱构建方法的重点通常是估计空间配准，以便基于人群数据计算均值/中位数形状或图像。在这项工作中，我们专注于在实现空间配准后对人群数据进行统计描述。我们引入并提出使用加权函数箱线图。这允许将中位数、百分位数或异常值等概念推广到数据对象为函数、形状或图像的空间，并允许基于核回归进行时空图谱构建。在我们的实验中，我们演示了该方法在构建儿科上呼吸道和胼胝体统计图谱方面的实用性，揭示了它们的生长模式。我们还基于儿科气道图谱定义了一个评分系统，用于定量测量气道中的声门下狭窄（SGS）严重程度。该评分可对气道手术前后的 SGS 患者和影像学正常对照进行分类。实验结果表明，图谱信息可用于评估气道手术对儿童的影响。
