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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Lung tumor segmentation in PET images using graph cuts
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Lung tumor segmentation in PET images using graph cuts

机译：使用图割在PET图像中进行肺肿瘤分割

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摘要

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill. ? 2012 Elsevier Ireland Ltd.
机译：在正电子发射断层扫描（PET）中分割肿瘤区域的目的是提供比单独的视觉评估更准确的肿瘤尺寸和扩展到相邻结构的测量，从而改善患者管理决策。我们为图割技术提出了一种分割能量函数，以改善PET的肺肿瘤分割。我们的分割能量基于对PET图像中的肿瘤体素的分析，并结合了标准摄取值（SUV）成本函数和单调的下坡SUV功能。单调的下坡特征避免了PET示踪剂摄取比肿瘤更高或更多的PET示踪剂吸收，从而避免分段泄漏到周围组织中，并且SUV成本函数改善了边界定义，还解决了肺肿瘤异质性的情况。我们在42例非小细胞肺癌（NSCLC）患者的临床PET量中评估了该方法。与区域增长方法，分水岭技术，fuzzy-c-means，基于区域的活动轮廓线和定制的下坡肿瘤相比，我们的方法可以改善分割效果，并且效果更好。 ？ 2012爱思唯尔爱尔兰有限公司

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