Petersen Jens, Nielsen Mads, Lo Pechin, Saghir Zaigham, Dirksen Asger, de Bruijne Marleen
Department of Computer Science, University of Copenhagen, Denmark.
Inf Process Med Imaging. 2011;22:49-60. doi: 10.1007/978-3-642-22092-0_5.
This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for surfaces with high curvature or complex shapes but the proposed columns, based on properly generated flow lines, which are non-intersecting, guarantee solutions that do not self-intersect and are better able to handle such surfaces. The method is applied to segment human airway walls in computed tomography images. Comparison with manual annotations on 649 cross-sectional images from 15 different subjects shows significantly smaller contour distances and larger area of overlap than are obtained with recently published graph based methods. Airway abnormality measurements obtained with the method on 480 scan pairs from a lung cancer screening trial are reproducible and correlate significantly with lung function.
本文介绍了一种新颖的最优图形构建方法，该方法适用于多维、多表面分割问题。此类问题通常通过在图形列所给定的空间内细化初始粗糙表面来解决。传统的列不太适合高曲率或复杂形状的表面，但所提出的基于适当生成的、不相交的流线的列，保证了不会自相交的解决方案，并且能够更好地处理此类表面。该方法应用于计算机断层扫描图像中人体气道壁的分割。与来自15个不同受试者的649幅横截面图像上的手动标注进行比较，结果表明，与最近发表的基于图形的方法相比，轮廓距离显著更小，重叠面积更大。在肺癌筛查试验的480对扫描中，用该方法获得的气道异常测量结果具有可重复性，并且与肺功能显著相关。
