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Automated detection of lung nodules in computed tomography images: a review

机译:在计算机断层扫描图像中自动检测肺结节:综述

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Lung nodules refer to a range of lung abnormalities the detection of which can facilitate early treatment for lung patients. Lung nodules can be detected by radiologists through examining lung images. Automated detection systems that locate nodules of various sizes within lung images can assist radiologists in their decision making. This paper presents a study of the existing methods on automated lung nodule detection. It introduces a generic structure for lung nodule detection that can be used to represent and describe the existing methods. The structure consists of a number of components including: acquisition, pre-processing, lung segmentation, nodule detection, and false positives reduction. The paper describes the algorithms used to realise each component in different systems. It also provides a comparison of the performance of the existing approaches.
机译:肺结节是指一系列肺部异常,对其检测可以促进肺部患者的早期治疗。放射科医生可以通过检查肺部图像来检测肺结节。在肺部图像中定位各种大小结节的自动检测系统可以帮助放射科医生做出决策。本文介绍了自动肺结节检测的现有方法的研究。它介绍了用于肺结节检测的通用结构,可用于表示和描述现有方法。该结构由许多组件组成,包括:采集,预处理,肺分割,结节检测和假阳性减少。本文介绍了用于实现不同系统中每个组件的算法。它还提供了现有方法性能的比较。

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