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Pulmonary nodule detection in medical images: A survey

机译:医学影像中的肺结节检测:一项调查

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Malignant nodules may be due to primary tumors or a metastasis and, given the importance of diagnosing early primary lung tumors, the detection of pulmonary nodules is critical. Therefore, a lot of research efforts have been devoted to the research on computer-aided detection (CADe) schemes for pulmonary nodule detection. This survey sheds light on what CADe schemes are really implementing to detect pulmonary nodules and which will in turn assist radiologist for better diagnosis. This paper provides a systematic depiction of both feature engineering- and deep learning-based CADe schemes, including the categories of pulmonary nodules, modalities of chest medical imaging, commonly used datasets with nodule annotations, and related publications in recent years. A comprehensive comparison and analyses of pulmonary nodule detection schemes proposed in the last three years are also presented. (C) 2018 Elsevier Ltd. All rights reserved.
机译:恶性结节可能是由于原发肿瘤或转移引起的,考虑到诊断早期原发性肺部肿瘤的重要性,肺结节的检测至关重要。因此,许多研究工作已经致力于用于肺结节检测的计算机辅助检测(CADe)方案的研究。这项调查揭示了CADe计划真正用于检测肺结节的方法,这将反过来帮助放射科医生更好地诊断。本文提供了基于特征工程和基于深度学习的CADe方案的系统描述,包括肺结节的类别,胸部医学成像的方式,带有结节注释的常用数据集以及近年来的相关出版物。还介绍了最近三年提出的肺结节检测方案的全面比较和分析。 (C)2018 Elsevier Ltd.保留所有权利。

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