Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions.
Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions.
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DOI：
10.1088/0031-9155/58/12/4071
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发表时间：
2013-06-21
影响因子：
3.5
通讯作者：
Dawant BM
中科院分区：
文献类型：
--
作者：
Deeley MA;Chen A;Datteri RD;Noble J;Cmelak A;Donnelly E;Malcolm A;Moretti L;Jaboin J;Niermann K;Yang ES;Yu DS;Dawant BM
图像分割已成为现代放射治疗计划中至关重要且通常限制速率的步骤。近年来，算法开发的速度和范围，甚至引入临床，都远远超过了评估性研究。在这项工作中，我们基于之前对配准驱动分割算法的评估，在 8 位专家评估者和 20 名接受脑部大型占位性肿瘤放射治疗的患者的背景下进行评估。在这项工作中，我们在随机单盲研究中测试了关于手动分割编辑影响的四种假设。我们使用 Dice 相似系数、体积和符号欧几里得距离误差在脑干、视交叉、眼睛和视神经的正常结构上测试了这些假设，以评估编辑对评估者间方差和准确性的影响。精度分析依赖于两种模拟的地面实况估计方法：STAPLE 和概率图的新颖实现。向专家们展示了我们之前研究中自动进行的、他们自己的和他们同行的细分，以供编辑。我们发现，无论来源如何，编辑减少了评估者间的方差，同时保持或提高了准确性并提高了效率，轮廓绘制时间至少减少了 60%。在评估者从头开始绘制轮廓效果不佳的区域，自动分割的编辑将总解剖缺失的发生率从地面真实估计中包含的总切片的大约 16% 降低到 8%。这些发现表明，轮廓编辑可能有助于建立共识，例如制定描绘标准，并且自动化方法甚至可能不太复杂的地图集都可以提高效率、评估者间方差和准确性。
Image segmentation has become a vital and often rate limiting step in modern radiotherapy treatment planning. In recent years the pace and scope of algorithm development, and even introduction into the clinic, have far exceeded evaluative studies. In this work we build upon our previous evaluation of a registration driven segmentation algorithm in the context of 8 expert raters and 20 patients who underwent radiotherapy for large space-occupying tumors in the brain. In this work we tested four hypotheses concerning the impact of manual segmentation editing in a randomized single-blinded study. We tested these hypotheses on the normal structures of the brainstem, optic chiasm, eyes and optic nerves using the Dice similarity coefficient, volume, and signed Euclidean distance error to evaluate the impact of editing on inter-rater variance and accuracy. Accuracy analyses relied on two simulated ground truth estimation methods: STAPLE and a novel implementation of probability maps. The experts were presented with automatic, their own, and their peers’ segmentations from our previous study to edit. We found, independent of source, editing reduced inter-rater variance while maintaining or improving accuracy and improving efficiency with at least 60% reduction in contouring time. In areas where raters performed poorly contouring from scratch, editing of the automatic segmentations reduced the prevalence of total anatomical miss from approximately 16% to 8% of the total slices contained within the ground truth estimations. These findings suggest that contour editing could be useful for consensus building such as in developing delineation standards, and that both automated methods and even perhaps less sophisticated atlases could improve efficiency, inter-rater variance, and accuracy.
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影响因子：
10.6
作者：
Warfield, SK;Zou, KH;Wells, WM
通讯作者：
Wells, WM
影响因子：
10.9
作者：
Noble, Jack H.;Dawant, Benoit M.
通讯作者：
Dawant, Benoit M.
DOI：
10.1007/s11548-007-0125-1
发表时间：
2007-12-01
影响因子：
3
作者：
Popovic, Aleksandra;de la Fuente, Matias;Radermacher, Klaus
通讯作者：
Radermacher, Klaus
DOI：
10.1007/978-3-642-33454-2_53
发表时间：
2012
期刊：
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
影响因子：
--
作者：
Asman, Andrew J.;Landman, Bennett A.
通讯作者：
Landman, Bennett A.
影响因子：
10.6
作者：
Cardoso, JS;Corte-Real, L
通讯作者：
Corte-Real, L