Interactive lung lobe segmentation and correction in tomographic images
Interactive lung lobe segmentation and correction in tomographic images
复制标题
断层扫描图像中的交互式肺叶分割和校正
DOI：
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发表时间：
2011
期刊：
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通讯作者：
H. Peitgen
中科院分区：
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作者：
Bianca Lassen;J. Kuhnigk;E. M. Rikxoort;H. Peitgen
断层图像的基于叶的量化对于诊断和监测肺部病理越来越感兴趣。随着现代断层扫描仪提供具有数百个切片的数据集，手动分割是耗时的，并且在临床常规中是不可行的。特别是对于具有特别临床重要性的严重肺部病理的患者，自动分割方法经常生成部分不准确甚至完全不可接受的结果。在这项工作中，我们提出了一种模态独立的，半自动化的方法，可用于任何现有的肺叶分割的通用校正和从头开始的分割。直观的基于切片的裂缝零件图用于引入用户知识。在内部，当前裂缝被表示为3D空间中的采样点，这些采样点被内插到裂缝表面。使用形态学处理，为每个用户绘制的2D曲线计算3D撞击区域。基于曲线和撞击区域，在每个交互步骤之后立即计算更新的叶边界表面以提供即时用户反馈。该方法进行了评价25正常剂量的CT扫描与人类观察者提供的参考标准。当从头开始分割时，使用平均5次相互作用和每例50秒的相互作用时间，到参考标准的平均距离为1.6 mm。当纠正不充分的自动分割时，初始误差从13.9 mm减少到1.9 mm。评估表明，给定分割的校正和从头开始的分割都可以在短时间内成功地进行，几乎没有交互。
Lobe-based quantification of tomographic images is of increasing interest for diagnosis and monitoring lung pathology. With modern tomography scanners providing data sets with hundreds of slices, manual segmentation is time-consuming and not feasible in the clinical routine. Especially for patients with severe lung pathology that are of particular clinical importance, automatic segmentation approaches frequently generate partially inaccurate or even completely unacceptable results. In this work we present a modality-independent, semi-automated method that can be used both for generic correction of any existing lung lobe segmentation and for segmentation from scratch. Intuitive slice-based drawing of fissure parts is used to introduce user knowledge. Internally, the current fissure is represented as sampling points in 3D space that are interpolated to a fissure surface. Using morphological processing, a 3D impact region is computed for each user-drawn 2D curve. Based on the curve and impact region, the updated lobar boundary surface is immediately computed after each interaction step to provide instant user feedback. The method was evaluated on 25 normal-dose CT scans with a reference standard provided by a human observer. When segmenting from scratch, the average distance to the reference standard was 1.6mm using an average of five interactions and 50 seconds of interaction time per case. When correcting inadequate automatic segmentations, the initial error was reduced from 13.9 to 1.9mm with comparable efforts. The evaluation shows that both correction of a given segmentation and segmentation from scratch can be successfully performed with little interaction in a short amount of time.