Performance evaluation of automatic anatomy segmentation algorithm on repeat or four-dimensional computed tomography images using deformable image registration method.
Performance evaluation of automatic anatomy segmentation algorithm on repeat or four-dimensional computed tomography images using deformable image registration method.
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DOI：
10.1016/j.ijrobp.2008.05.008
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发表时间：
2008-09-01
影响因子：
7
通讯作者：
Dong, Lei
中科院分区：
文献类型：
--
作者：
Wang, He;Adam, S. Garden;Zhang, Lifei;Wei, Xiong;Ahamad, Anesa;Kuban, Deborah A.;Komaki, Ritsuko;O'Daniel, Jennifer;Zhang, Yongbin;Mohan, Radhe;Dong, Lei
关键词：
感兴趣解剖区域（ROI）从计划CT到日常CT的自动传播是图像引导自适应放射治疗的重要步骤。本研究的目的是定量评价该算法在典型临床应用中的性能。我们先前采用了基于图像强度的变形配准算法来找到两幅图像之间的对应关系。在本研究中，使用相同的变换将计划CT图像上描绘的ROI映射到日常CT或四维（4D）CT图像上。为了提高算法的鲁棒性，采用了边界平滑和边界修正等后处理方法。使用体积重叠指数（VOI）和平均绝对表面-表面距离（ASSD），对8名头颈部患者（共100次重复CT）、1名前列腺患者（共24次重复CT）和9名肺癌患者（共90张4D-CT图像）的自动传播轮廓进行评价，以对比医生绘制的轮廓和医生修改的变形轮廓。在重复CT图像上，变形轮廓与日常解剖结构匹配良好。与独立绘制的轮廓相比，VOI和平均ASSD分别为83%和1.3 mm。如果仅要求医生纠正变形轮廓，则实现了更好的一致性（大于97%且小于0.4 mm）。该算法在图像中存在随机噪声的情况下具有鲁棒性。可变形算法可能是将计划ROI传播到后续变化解剖结构的CT图像的有效方法，但强烈建议由医生进行最终审查。
Auto-propagation of anatomical region-of-interests (ROIs) from the planning CT to daily CT is an essential step in image-guided adaptive radiotherapy. The goal of this study was to quantitatively evaluate the performance of the algorithm in typical clinical applications. We previously adopted an image intensity-based deformable registration algorithm to find the correspondence between two images. In this study, the ROIs delineated on the planning CT image were mapped onto daily CT or four-dimentional (4D) CT images using the same transformation. Post-processing methods, such as boundary smoothing and modification, were used to enhance the robustness of the algorithm. Auto-propagated contours for eight head-and-neck patients with a total of 100 repeat CTs, one prostate patient with 24 repeat CTs, and nine lung cancer patients with a total of 90 4D-CT images were evaluated against physician-drawn contours and physician-modified deformed contours using the volume-overlap-index (VOI) and mean absolute surface-to-surface distance (ASSD). The deformed contours were reasonably well matched with daily anatomy on repeat CT images. The VOI and mean ASSD were 83% and 1.3 mm when compared to the independently drawn contours. A better agreement (greater than 97% and less than 0.4 mm) was achieved if the physician was only asked to correct the deformed contours. The algorithm was robust in the presence of random noise in the image. The deformable algorithm may be an effective method to propagate the planning ROIs to subsequent CT images of changed anatomy, although a final review by physicians is highly recommended.
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影响因子：
4.8
作者：
Goldberg-Zimring, D;Talos, IF;Zou, KH
通讯作者：
Zou, KH
DOI：
10.1016/s0360-3016(02)02884-5
发表时间：
2002-08-01
影响因子：
7
作者：
Jaffray, DA;Siewerdsen, JH;Martinez, AA
通讯作者：
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DOI：
10.1016/j.ijrobp.2004.11.033
发表时间：
2005-03-15
影响因子：
7
作者：
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通讯作者：
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影响因子：
3.5
作者：
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通讯作者：
Van Dyk, J
DOI：
10.1016/j.ijrobp.2006.12.039
发表时间：
2007-07-01
影响因子：
7
作者：
Breen, Stephen L.;Publicover, Julia;Waldron, John
通讯作者：
Waldron, John