Mullally William, Betke Margrit, Wang Jingbin, Ko Jane P
Computer Science Department, Boston University, Boston, Massachusetts 02215, USA.
Med Phys. 2004 Apr;31(4):839-48. doi: 10.1118/1.1656593.
Several segmentation methods to evaluate growth of small isolated pulmonary nodules on chest computed tomography (CT) are presented. The segmentation methods are based on adaptively thresholding attenuation levels and use measures of nodule shape. The segmentation methods were first tested on a realistic chest phantom to evaluate their performance with respect to specific nodule characteristics. The segmentation methods were also tested on sequential CT scans of patients. The methods' estimation of nodule growth were compared to the volume change calculated by a chest radiologist. The best method segmented nodules on average 43% smaller or larger than the actual nodule when errors were computed across all nodule variations on the phantom. Some methods achieved smaller errors when examined with respect to certain nodule properties. In particular, on the phantom individual methods segmented solid nodules to within 23% of their actual size and nodules with 60.7 mm3 volumes to within 14%. On the clinical data, none of the methods examined showed a statistically significant difference in growth estimation from the radiologist.
本文介绍了几种用于评估胸部计算机断层扫描(CT)上孤立性小肺结节生长情况的分割方法。这些分割方法基于对衰减水平的自适应阈值处理,并使用结节形状的测量指标。首先在逼真的胸部体模上对分割方法进行测试,以评估其在特定结节特征方面的性能。还在患者的连续CT扫描上对分割方法进行了测试。将这些方法对结节生长的估计与胸部放射科医生计算的体积变化进行比较。当在体模上对所有结节变化计算误差时,最佳方法分割出的结节平均比实际结节小或大43%。就某些结节属性进行检查时,一些方法的误差较小。特别是,在体模上,个别方法将实性结节分割至其实际大小的23%以内,将体积为60.7立方毫米的结节分割至14%以内。在临床数据方面,所检查的方法中没有一种在生长估计方面与放射科医生有统计学上的显著差异。