| 影像组学中特征提取研究进展 |
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| 引用本文： | 谢凯,孙鸿飞,林涛,高留刚,眭建锋,倪昕晔. 影像组学中特征提取研究进展[J]. 中国医学影像技术, 2017, 33(12): 1792-1796 |
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| 作者姓名： | 谢凯 孙鸿飞 林涛 高留刚 眭建锋 倪昕晔 |
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| 作者单位： | 南京医科大学附属常州第二人民医院放疗科, 江苏 常州 213003,南京医科大学附属常州第二人民医院放疗科, 江苏 常州 213003,南京医科大学附属常州第二人民医院放疗科, 江苏 常州 213003,南京医科大学附属常州第二人民医院放疗科, 江苏 常州 213003,南京医科大学附属常州第二人民医院放疗科, 江苏 常州 213003,南京医科大学附属常州第二人民医院放疗科, 江苏 常州 213003 |
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| 基金项目： | 江苏省自然科学基金（BK20151181）、常州市社会发展项目（CJ20160029）、常州市卫生高层次人才资助项目（2016CZLJ004）。 |
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| 摘 要： | 影像组学是从CT、MRI、PET等医学影像的ROI提取大量影像特征，来描述肿瘤生物学特征和异质性等信息的一种定量分析方法。随着数据科学发展，影像组学的研究方法日益受到国内外的重视。影像组学的特征提取是其中的重要步骤。本文对影像组学的特征提取进行综述。
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| 关 键 词： | 影像组学 异质性 诊断 特征提取 |
| 收稿时间： | 2017-07-06 |
| 修稿时间： | 2017-11-03 |
Research progresses in feature extraction of radiomics |
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| XIE Kai,SUN Hongfei,LIN Tao,GAO Liugang,SUI Jianfeng and NI Xinye. Research progresses in feature extraction of radiomics[J]. Chinese Journal of Medical Imaging Technology, 2017, 33(12): 1792-1796 |
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| Authors: | XIE Kai SUN Hongfei LIN Tao GAO Liugang SUI Jianfeng NI Xinye |
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| Affiliation: | Department of Radiation Oncology, the Second People''s Hospital of ChangzhouAffiliated to Nanjing Medical University, Changzhou 213003, China,Department of Radiation Oncology, the Second People''s Hospital of ChangzhouAffiliated to Nanjing Medical University, Changzhou 213003, China,Department of Radiation Oncology, the Second People''s Hospital of ChangzhouAffiliated to Nanjing Medical University, Changzhou 213003, China,Department of Radiation Oncology, the Second People''s Hospital of ChangzhouAffiliated to Nanjing Medical University, Changzhou 213003, China,Department of Radiation Oncology, the Second People''s Hospital of ChangzhouAffiliated to Nanjing Medical University, Changzhou 213003, China and Department of Radiation Oncology, the Second People''s Hospital of ChangzhouAffiliated to Nanjing Medical University, Changzhou 213003, China |
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| Abstract: | Radiomics refers to the comprehensive quantification of information such as tumor biological feature and heterogeneity through assessing a large number of quantitative image features from ROI of CT, MRI and PET images. With the development of data science, radiomics has been paid more and more attention. Feature extraction is an important step of Radiomics. The processes in feature extraction of radiomics were reviewed in this paper. |
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| Keywords: | Radiomics Heterogeneity Diagnosis Feature extraction |
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