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基于种子生成方案和随机游走的肺癌患者器官轮廓生成。

Organ Contouring for Lung Cancer Patients with a Seed Generation Scheme and Random Walks.

机构信息

Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung City 40402, Taiwan.

Department of Diagnostic Radiology, Singapore General Hospital, Singapore 169608, Singapore.

出版信息

Sensors (Basel). 2020 Aug 26;20(17):4823. doi: 10.3390/s20174823.

Abstract

In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring.

摘要

在这项研究中,我们提出了一种用于非小细胞肺癌放射治疗计划的半自动交互式器官轮廓勾画方法。我们勾画了几个器官,包括肺、气道、心脏、脊髓、身体和大体肿瘤体积(GTV)。我们提出了一些方案来自动生成和消失随机游走(RW)算法的种子。我们考虑了 25 名来自中国医科大学附属医院(CMUH)的肺癌患者,其 CT 图像来自台湾台中的 CMUH。临床肿瘤学家制作的手动轮廓被用作比较的金标准,以评估我们提出的方法的性能。计算同一器官的两个轮廓之间的 Dice 系数以评估相似性。肺、气道、心脏、脊髓和身体以及 GTV 分割的平均 Dice 系数分别为 0.92、0.84、0.83、0.73、0.85 和 0.66。整个 CT 序列分割的计算时间在 2 到 4 分钟之间。结果表明,我们的方法有可能通过在轮廓勾画方面节省大量时间,来协助 CMUH 的肿瘤学家进行放射治疗过程,并有望在其他医院也能如此。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/887f/7506591/4246ba40161b/sensors-20-04823-g001.jpg

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