Cates Joshua E, Whitaker Ross T, Jones Greg M
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
Med Image Anal. 2005 Dec;9(6):566-78. doi: 10.1016/j.media.2005.04.007.
This paper evaluates the effectiveness of an interactive, three-dimensional image segmentation technique that relies on watersheds. This paper presents two user-based case studies, which include two different groups of domain experts. Subjects manipulate a graphics-based front end to a hierarchy of segmented regions generated from a watershed segmentation algorithm, which is implemented in the Insight Toolkit. In the first study, medical students segment several different anatomical structures from the Visible Human Female head and neck color cryosection data. In the second study, radiologists use the interactive tool to produce models of brain tumors from MRI data. This paper presents a quantitative and qualitative comparison against hand contouring. To quantify accuracy, we estimate ground truth from the hand-contouring data using the Simultaneous Truth and Performance Estimation algorithm. We also apply metrics from the literature to estimate precision and efficiency. The watershed segmentation technique showed improved subject interaction times and increased inter-subject precision over hand contouring, with quality that is visually and statistically comparable. The analysis also identifies some failures in the watershed technique, where edges were poorly defined in the data, and note a trend in the hand-contouring results toward systematically larger segmentations, which raises questions about the wisdom of using expert segmentations to define ground truth.
本文评估了一种基于分水岭算法的交互式三维图像分割技术的有效性。本文展示了两个基于用户的案例研究，其中包括两组不同的领域专家。受试者通过一个基于图形的前端来操作由分水岭分割算法生成的分割区域层次结构，该算法在Insight Toolkit中实现。在第一个研究中，医学生从可视人女性头部和颈部彩色冷冻切片数据中分割出几种不同的解剖结构。在第二个研究中，放射科医生使用该交互式工具从MRI数据生成脑肿瘤模型。本文给出了与手工勾勒轮廓的定量和定性比较。为了量化准确性，我们使用同步真值和性能估计算法从手工勾勒轮廓数据中估计真值。我们还应用文献中的指标来估计精度和效率。与手工勾勒轮廓相比，分水岭分割技术显示出受试者交互时间缩短，受试者间精度提高，质量在视觉和统计上具有可比性。分析还识别出分水岭技术中的一些失败情况，即数据中的边缘定义不佳，并注意到手工勾勒轮廓结果中存在系统性更大分割的趋势，这引发了关于使用专家分割来定义真值是否明智的问题。
