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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 >Automatic 3D pulmonary nodule detection in CT images: A survey
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Automatic 3D pulmonary nodule detection in CT images: A survey

机译：CT图像中3D肺结节的自动检测：一项调查

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This work presents a systematic review of techniques for the 3D automatic detection of pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze the latest technology being used for the development of computational diagnostic tools to assist in the acquisition, storage and, mainly, processing and analysis of the biomedical data. Also, this work identifies the progress made, so far, evaluates the challenges to be overcome and provides an analysis of future prospects. As far as the authors know, this is the first time that a review is devoted exclusively to automated 3D techniques for the detection of pulmonary nodules from lung CT images, which makes this work of noteworthy value. The research covered the published works in the Web of Science, PubMed, Science Direct and IEEEXplore up to December 2014. Each work found that referred to automated 3D segmentation of the lungs was individually analyzed to identify its objective, methodology and results. Based on the analysis of the selected works, several studies were seen to be useful for the construction of medical diagnostic aid tools. However, there are certain aspects that still require attention such as increasing algorithm sensitivity, reducing the number of false positives, improving and optimizing the algorithm detection of different kinds of nodules with different sizes and shapes and, finally, the ability to integrate with the Electronic Medical Record Systems and Picture Archiving and Communication Systems. Based on this analysis, we can say that further research is needed to develop current techniques and that new algorithms are needed to overcome the identified drawbacks. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
机译：这项工作提出了对计算机断层扫描（CT）图像中的3D肺结节自动检测技术的系统综述。它的主要目标是分析用于开发计算诊断工具的最新技术，以协助获取，存储生物医学数据，主要是协助处理和分析生物医学数据。此外，这项工作还可以确定迄今取得的进展，评估需要克服的挑战并提供对未来前景的分析。据作者所知，这是第一次专门针对从肺部CT图像检测肺结节的自动化3D技术进行的综述，这使得这项工作具有重要的价值。这项研究涵盖了截至2014年12月在Web of Science，PubMed，Science Direct和IEEEXplore上发表的作品。每项研究都发现，对涉及肺部3D自动分割的文献进行了单独分析，以确定其目的，方法和结果。根据对选定作品的分析，发现一些研究对构建医疗诊断辅助工具很有用。但是，仍然需要注意某些方面，例如提高算法敏感性，减少误报数量，改进和优化对具有不同大小和形状的不同种类结节的算法检测，以及最终与电子技术集成的能力。医疗记录系统以及图片存档和通信系统。基于此分析，我们可以说需要进一步研究以开发当前技术，并且需要新算法来克服已发现的缺点。 （C）2015 Elsevier Ireland Ltd.保留所有权利。

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