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CT影像组学在肺癌诊治中应用的研究进展和问题探索

Radiomics, a technology based on multimodal medical image processing and analysis, is able to extract automatically and analyze massive data from computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography/computed tomography (PET/CT) via high-performance computer algori...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 中国肺癌杂志编辑部 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583873/
https://www.ncbi.nlm.nih.gov/pubmed/32798440
http://dx.doi.org/10.3779/j.issn.1009-3419.2020.101.36
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description Radiomics, a technology based on multimodal medical image processing and analysis, is able to extract automatically and analyze massive data from computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography/computed tomography (PET/CT) via high-performance computer algorithm in order to pursue early diagnosis of disease, benign and malignant tumor discrimination, dynamic evaluation of disease treatment, and individualized precision therapy. To date, many studies demonstrate that radiomics not only has great potential in early diagnosis of lung cancer and prediction of genotype, treatment efficacy, as well as prognosis but also is based on imaging methods that are noninvasive, inexpensive, and repeatable. It does demonstrate precious values in guiding the clinical diagnosis and treatment of lung cancer, especially in the personalized and precise treatments and researches of lung cancer. However, the consistency and reproducibility of radiomics and the selection of robust characteristics still warrant further researches.
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spelling pubmed-75838732020-11-02 CT影像组学在肺癌诊治中应用的研究进展和问题探索 Zhongguo Fei Ai Za Zhi 综述 Radiomics, a technology based on multimodal medical image processing and analysis, is able to extract automatically and analyze massive data from computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography/computed tomography (PET/CT) via high-performance computer algorithm in order to pursue early diagnosis of disease, benign and malignant tumor discrimination, dynamic evaluation of disease treatment, and individualized precision therapy. To date, many studies demonstrate that radiomics not only has great potential in early diagnosis of lung cancer and prediction of genotype, treatment efficacy, as well as prognosis but also is based on imaging methods that are noninvasive, inexpensive, and repeatable. It does demonstrate precious values in guiding the clinical diagnosis and treatment of lung cancer, especially in the personalized and precise treatments and researches of lung cancer. However, the consistency and reproducibility of radiomics and the selection of robust characteristics still warrant further researches. 中国肺癌杂志编辑部 2020-10-20 /pmc/articles/PMC7583873/ /pubmed/32798440 http://dx.doi.org/10.3779/j.issn.1009-3419.2020.101.36 Text en 版权所有©《中国肺癌杂志》编辑部2020 This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/.
spellingShingle 综述
CT影像组学在肺癌诊治中应用的研究进展和问题探索
title CT影像组学在肺癌诊治中应用的研究进展和问题探索
title_full CT影像组学在肺癌诊治中应用的研究进展和问题探索
title_fullStr CT影像组学在肺癌诊治中应用的研究进展和问题探索
title_full_unstemmed CT影像组学在肺癌诊治中应用的研究进展和问题探索
title_short CT影像组学在肺癌诊治中应用的研究进展和问题探索
title_sort ct影像组学在肺癌诊治中应用的研究进展和问题探索
topic 综述
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583873/
https://www.ncbi.nlm.nih.gov/pubmed/32798440
http://dx.doi.org/10.3779/j.issn.1009-3419.2020.101.36
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