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首页> 外文会议>Conference on Medical Imaging 2008: Imaging Processing; 20080217-19; San Diego,CA(US) >4DCT Image-Based Lung Motion Field Extraction and Analysis
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4DCT Image-Based Lung Motion Field Extraction and Analysis

机译：基于4DCT图像的肺运动场提取与分析

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摘要

Respiratory motion is a complicating factor in radiation therapy, tumor ablation, and other treatments of the thorax and upper abdomen. In most cases, the treatment requires a demanding knowledge of the location of the organ under investigation. One approach to reduce the uncertainty of organ motion caused by breathing is to use prior knowledge of the breathing motion. In this work, we extract lung motion fields of seven patients in 4DCT inhale-exhale images using an iterative shape-constrained deformable model approach. Since data was acquired for radiotherapy planning, images of the same patient over different weeks of treatment were available. Although, respiratory motion shows a repetitive character, it is well-known that patient's variability in breathing pattern impedes motion estimation. A detailed motion field analysis is performed in order to investigate the reproducibility of breathing motion over the weeks of treatment. For that purpose, parameters being significant for breathing motion are derived. The analysis of the extracted motion fields provides a basis for a further breathing motion prediction. Patient-specific motion models are derived by averaging the extracted motion fields of each individual patient. The obtained motion models are adapted to each patient in a leave-one-out test in order to simulate motion estimation to unseen data. By using patient-specific mean motion models 60% of the breathing motion can be captured on average.
机译：呼吸运动是放疗，肿瘤消融以及胸及上腹部的其他治疗中的复杂因素。在大多数情况下，治疗需要对所研究器官的位置有严格的了解。减少由呼吸引起的器官运动的不确定性的一种方法是使用呼吸运动的先验知识。在这项工作中，我们使用迭代形状约束可变形模型方法在4DCT吸气-呼气图像中提取7名患者的肺运动场。由于获取了放射治疗计划的数据，因此可获得同一患者在不同治疗周的图像。尽管呼吸运动表现出重复性，但是众所周知，患者呼吸模式的可变性会阻碍运动估计。进行了详细的运动场分析，以研究在治疗周内呼吸运动的再现性。为此，导出对于呼吸运动重要的参数。提取的运动场的分析为进一步的呼吸运动预测提供了基础。通过平均每个患者的提取运动场，可以得出患者特定的运动模型。所获得的运动模型在“留一法”测试中适用于每位患者，以便将运动估计模拟为看不见的数据。通过使用患者特定的平均运动模型，平均可以捕获到60％的呼吸运动。

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