Bol Gijsbert H, Kotte Alexis N T J, van der Heide Uulke A, Lagendijk Jan J W
Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
Comput Methods Programs Biomed. 2009 Nov;96(2):133-40. doi: 10.1016/j.cmpb.2009.04.008. Epub 2009 May 13.
The delineation of tumors and their surrounding organs at risk is a critical step of the treatment planning for radiation therapy. Besides computer tomography (CT), other imaging modalities are used to improve the quality of the delineations, such as magnetic resonance imaging (MRI) and positron emission tomography (PET). A practical framework is presented for using multiple datasets from different modalities during the delineation phase. The system is based on two basic principles. First, all image datasets of all available modalities are displayed in their original form (in their own coordinate system, with their own spatial resolution and voxel aspect ratio), and second, delineations can take place on all orthogonal views of each dataset and changes made to a delineation are visualized in all image sets, giving direct feedback to the delineator. The major difference between the described approach and other existing delineation tools is that instead of resampling the image sets, the delineations are transformed from one dataset to another. The transformation used for transferring the delineations is obtained by rigid normalized mutual information registration. The crucial components and the benefits of the application are presented and discussed.
肿瘤及其周围危险器官的勾画是放射治疗治疗计划的关键步骤。除了计算机断层扫描（CT）外，还使用其他成像模态来提高勾画质量，如磁共振成像（MRI）和正电子发射断层扫描（PET）。本文提出了一个在勾画阶段使用来自不同模态的多个数据集的实用框架。该系统基于两个基本原则。第一，所有可用模态的所有图像数据集都以其原始形式显示（在其自己的坐标系中，具有其自己的空间分辨率和体素长宽比），第二，可以在每个数据集的所有正交视图上进行勾画，并且对勾画所做的更改会在所有图像集中可视化，从而为勾画者提供直接反馈。所描述的方法与其他现有勾画工具之间的主要区别在于，不是对图像集进行重采样，而是将勾画从一个数据集转换到另一个数据集。用于传输勾画的变换是通过刚性归一化互信息配准获得的。本文介绍并讨论了该应用的关键组件和优点。
