摘要
肺癌是我国最常见的癌症类型,也是癌症死亡的主要疾病,肺癌的早期发现和早期诊断是降低肺癌死亡率,提高患者生活质量最关键的环节。传统影像学技术在肺结节良恶性鉴别诊断中存在一定的局限性,随着人工智能在医学诊疗领域的不断深入,影像组学、深度学习以及多模态融合模型对肺结节良恶性诊断产生了重要价值。本文就传统影像学技术到人工智能在肺癌早期诊断中的相关研究进展进行综述。
Lung cancer is the most common type of cancer in our country and the main disease of cancer death.Early detection and early diagnosis of lung cancer is the most critical link to reduce lung cancer mortality and improve the quality of life of patients.Traditional imaging techniques have certain limitations in the differential diagnosis of benign and malignant pulmonary nodules.With the continuous deepening of artificial intelligence in the field of medical diagnosis and treatment,radiomics,deep learning and multimodal fusion models have produced important value in the diagnosis of benign and malignant lung nodules.This article reviews the research progress from traditional imaging technology to artificial intelligence in the early diagnosis of lung cancer.
作者
马婷婷
许志高
Ma Tingting;Xu Zhigao(Changzhi Medical College,Changzhi,Shanxi 046000,China;Datong Third People’s Hospital,Datong,Shanxi 037000,China)
出处
《齐齐哈尔医学院学报》
2025年第24期2387-2392,共6页
Journal of Qiqihar Medical University
基金
山西省医学重点科研项目(2023XM057)。
关键词
肺结节
影像组学
深度学习
Pulmonary nodules
Radiomics
Deep learning
