Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA.
Med Image Anal. 2011 Dec;15(6):877-84. doi: 10.1016/j.media.2011.05.001. Epub 2011 May 12.
In recent years, radiation therapy has become the preferred treatment for many types of head and neck tumors. To plan the procedure, vital structures, including the optic nerves and chiasm, must be identified using CT/MR imagery. In this work we present a novel method for automatically localizing the optic nerves and chiasm using a tubular structure localization algorithm in which a statistical model and image registration are used to incorporate a priori local intensity and shape information. The method results in mean Dice coefficients of 0.8 when compared to manual segmentations over ten test cases. This suggests that our method is more accurate than existing techniques developed for the segmentation of these structures.
近年来，放射疗法已成为许多头颈部肿瘤的首选治疗方法。为了规划治疗方案，必须使用 CT/MR 图像识别出包括视神经和视交叉在内的重要结构。在这项工作中，我们提出了一种使用管状结构定位算法自动定位视神经和视交叉的新方法，该算法使用统计模型和图像配准来合并先验局部强度和形状信息。与针对这些结构分割开发的现有技术相比，该方法在十个测试案例中的平均 Dice 系数达到了 0.8。这表明我们的方法比现有的技术更准确。
