• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Journal of Applied Clinical Medical Physics >Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors
【2h】

Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors

机译：脑肿瘤放疗中CT和MR图像配准的标准化互信息方法的临床验证

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Image registration integrates information from different imaging modalities and has the potential to improve determination of target volume in radiotherapy planning. This paper describes the implementation and validation of a 3D fully automated registration procedure in the process of radiotherapy treatment planning of brain tumors. Fifteen patients with various brain tumors received computed tomography (CT) and magnetic resonance (MR) brain imaging before the start of radiotherapy. First, the normalized mutual information (NMI) method was used for image registration. Registration accuracy was estimated by performing statistical analysis of coordinate differences between CT and MR anatomical landmarks along the x‐, y‐ and z‐axes. Second, a visual validation protocol was developed to validate the quality of individual registration solutions, and this protocol was tested in a series of 36 CT‐MR registration procedures with intentionally applied registration errors. The mean coordinate differences between CT and MR landmarks along the x‐ and y‐axes were in general within 0.5 mm. The mean coordinate differences along the z‐axis were within 1.0 mm, which is of the same magnitude as the applied slice thickness in scanning. In addition, the detection of intentionally applied registration errors by employment of a standardized visual validation protocol resulted in low false‐negative and low false‐positive rates. Application of the NMI method for the brain results in excellent automatic registration accuracy, and the method has been incorporated into the daily routine at our institution. A standardized validation protocol ensures the quality of individual registrations by detecting registration errors with high sensitivity and specificity. This protocol is proposed for the validation of other linear registration methods.PACS numbers: 87.53.Xd, 87.57.Gg
机译：图像配准整合了来自不同成像方式的信息，并具有改善放射治疗计划中目标体积确定的潜力。本文介绍了在脑肿瘤放射治疗计划过程中3D全自动注册程序的实施和验证。在开始放疗之前，有15位患有各种脑肿瘤的患者接受了计算机断层扫描（CT）和磁共振（MR）脑成像。首先，使用归一化互信息（NMI）方法进行图像配准。通过对沿x轴，y轴和z轴的CT和MR解剖界标之间的坐标差异进行统计分析来估计配准精度。其次，开发了一种视觉验证协议来验证单个注册解决方案的质量，并在一系列36种CT-MR注册程序中对该协议进行了测试，并故意施加了注册错误。 CT和MR地标沿x和y轴的平均坐标差通常在0.5 mm之内。沿z轴的平均坐标差在1.0 mm以内，与在扫描中应用的切片厚度相同。此外，通过使用标准化的视觉验证协议来检测故意施加的注册错误会导致较低的假阴性率和较低的假阳性率。 NMI方法在大脑中的应用可实现出色的自动配准精度，并且该方法已被纳入我们机构的日常工作中。标准化的验证协议通过以高灵敏度和特异性检测注册错误来确保单个注册的质量。该协议用于验证其他线性配准方法.PACS编号：87.53.Xd，87.57.Gg

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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