ISSN 1004-4140
CN 11-3017/P
刘宇婷, 刘挨师. 影像组学在诊断肺结节中的研究进展[J]. CT理论与应用研究, 2023, 32(4): 573-578. DOI: 10.15953/j.ctta.2022.056.
引用本文: 刘宇婷, 刘挨师. 影像组学在诊断肺结节中的研究进展[J]. CT理论与应用研究, 2023, 32(4): 573-578. DOI: 10.15953/j.ctta.2022.056.
LIU Y T, LIU A S. Research Progress of Radiomics in the Diagnosis of Pulmonary Nodules[J]. CT Theory and Applications, 2023, 32(4): 573-578. DOI: 10.15953/j.ctta.2022.056. (in Chinese).
Citation: LIU Y T, LIU A S. Research Progress of Radiomics in the Diagnosis of Pulmonary Nodules[J]. CT Theory and Applications, 2023, 32(4): 573-578. DOI: 10.15953/j.ctta.2022.056. (in Chinese).

影像组学在诊断肺结节中的研究进展

Research Progress of Radiomics in the Diagnosis of Pulmonary Nodules

  • 摘要: 近年来随着医疗水平的发展,人们对自身健康的重视程度不断提高,使得肺结节等占位性病变能够被更早的检出,但在全球范围内,肺部恶性病变造成的死亡人数仍然在不断攀升且居高不下。影像组学是一个新兴的领域,旨从医学图像中获得自动定量成像特征,无创地预测结节和肿瘤行为。与传统的视觉图像特征相比,影像组学可以提取更多数量的结节特征,具有更好的重现性。科学系统地运用影像组学手段不仅能够防止过度的医疗行为,减轻患者经济负担,同时也能使肺部病变患者得到尽早的治疗以获得最佳的预后。

     

    Abstract: In recent years, with the continuous improvement of medical level, people pay more attention to their own health, pulmonary nodules and other space-occupying lesions can be detected earlier, but on a global scale, the number of deaths caused by malignant lung lesions Still rising and remaining high. Radiomics is an emerging field that aims to derive automated quantitative imaging features from medical images to noninvasively predict nodular and tumor behavior. Compared with traditional visual image features, radiomics can extract more nodular features with better reproducibility. The scientific and systematic use of radiomics can not only prevent excessive medical behaviors and reduce the economic burden of patients, but also enable patients with lung lesions to receive early treatment for the best prognosis.

     

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