...
首页> 外文期刊>Frontiers in Oncology >Clinical Evaluation of Commercial Atlas-Based Auto-Segmentation in the Head and Neck Region
【24h】

Clinical Evaluation of Commercial Atlas-Based Auto-Segmentation in the Head and Neck Region

机译:头部和颈部基于商业地图集的自动分割的临床评价

获取原文
           

摘要

Background: While atlas segmentation (AS) has proven to be a time-saving and promising method for radiation therapy contouring, optimal methods for its use have not been well-established. Therefore, we investigated the relationship between the size of the atlas patient population and the atlas segmentation auto contouring (AC) performance. Methods: A total of 110 patients' head planning CT images were selected. The mandible and thyroid were selected for this study. The mandibles and thyroids of the patient population were carefully segmented by two skilled clinicians. Of the 110 patients, 100 random patients were registered to 5 different atlas libraries as atlas patients, in groups of 20 to 100, with increments of 20. AS was conducted for each of the remaining 10 patients, either by simultaneous atlas segmentation (SAS) or independent atlas segmentation (IAS). The AS duration of each target patient was recorded. To validate the accuracy of the generated contours, auto contours were compared to manually generated contours (MC) using a volume-overlap-dependent metric, Dice Similarity Coefficient (DSC), and a distance-dependent metric, Hausdorff Distance (HD). Results: In both organs, as the population increased from n = 20 to n = 60, the results showed better convergence. Generally, independent cases produced better performance than simultaneous cases. For the mandible, the best performance was achieved by n = 60 [DSC = 0.92 (0.01) and HD = 6.73 (1.31) mm] and the worst by n = 100 [DSC = 0.90 (0.03) and HD = 10.10 (6.52) mm] atlas libraries. Similar results were achieved with the thyroid; the best performance was achieved by n = 60 [DSC = 0.79 (0.06) and HD = 10.17 (2.89) mm] and the worst by n = 100 [DSC = 0.72 (0.13) and HD = 12.88 (3.94) mm] atlas libraries. Both IAS and SAS showed similar results. Manual contouring of the mandible and thyroid required an average of 1,044 (±170.15) seconds, while AS required an average of 46.4 (±2.8) seconds. Conclusions: The performance of AS AC generally increased as the population of the atlas library increased. However, the performance does not drastically vary in the larger atlas libraries in contrast to the logic that bigger atlas library should lead to better results. In fact, the results do not vary significantly toward the larger atlas library. It is necessary for the institutions to independently research the optimal number of subjects.
机译:背景:虽然Atlas分割(AS)已被证明是一种节省时间和有希望的放射治疗轮廓的方法,但其使用的最佳方法尚未得到良好。因此,我们调查了阿特拉斯患者群体的大小与地图分割自动轮廓(AC)性能之间的关系。方法:选择110例患者的头部规划CT图像。选择该研究的下颌骨和甲状腺。患者群体的颌骨和甲状腺素被两个熟练的临床医生仔细分割。在110名患者中,100名随机患者将100名随机患者注册到5种不同的地图集文库,以20至100的一组,增量为20.如剩余的10名患者的每个患者进行,无论是通过同时的阿特拉斯分割(SAS)都是如此或独立的地图集分割(IAS)。记录每个目标患者的持续时间。为了验证所生成的轮廓的准确性,将自动轮廓与手动生成轮廓(MC)使用卷重叠依赖性度量,骰子相似度系数(DSC)和距离依赖性度量,HAUSDORFF距离(HD)进行比较。结果:在两个器官中,随着人口从n = 20增加到n = 60,结果表明了更好的收敛性。通常,独立案例产生的性能比同时案件更好。对于下颌骨,N = 60 [DSC = 0.92(0.01)和HD = 6.73(1.31)mm]实现了最佳性能,并且最差N = 100 [DSC = 0.090(0.03)和HD = 10.10(6.52) mm] atlas图书馆。用甲状腺达到类似的结果;通过n = 60 [DSC = 0.79(0.06)和HD = 10.17(2.89)mm]实现了最佳性能,并且最差N = 100 [DSC = 0.72(0.13)和HD = 12.88(3.94)mm] ATLAS库。 IAS和SA都显示出类似的结果。手动轮廓的下颌骨和甲状腺需要平均为1,044(±170.15)秒,而平均需要46.4(±2.8)秒。结论:随着阿特拉斯图书馆人口的增加,随着AC的表现通常增加。然而,与较大的Atlas库的逻辑相比,较大的阿特拉斯库在较大的阿特拉斯库应该导致更好的结果中,性能不会变化。事实上,结果对较大的地图集图书馆没有显着变化。该机构有必要独立研究最佳的科目。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号