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作 者:陈师 胡剑鹏[1] 徐伟[1] 张骥[1] 吴吉明[1] CHEN Shi;HU Jianpeng;XU Wei;ZHANG Ji;WU Jiming(Department of Thoracic and Cardiovascular Surgery,the First People′s Hospital of Changde City in Hunan Province,Changde415000,China)
机构地区:[1]湖南省常德市第一人民医院胸心血管外科,湖南常德415000
出 处:《中国现代医生》2021年第30期184-187,共4页China Modern Doctor
基 金:湖南省科技创新计划项目(2018SK50203);湖南省常德市科学技术局技术研究与开发资金项目(2018J020)。
摘 要:肺癌属于临床常见的恶性肿瘤之一,当前胸部CT是进行早期肺癌鉴别的重要方式,但是因其存在"异病同影"等情况,加之受到临床经验等因素影响,在病灶良恶性鉴别方面有较大差异,极易出现误诊或漏诊情况。近年来人工智能被逐渐应用于临床,其在肺结节良恶性鉴别方面也发挥着一定作用。本文从人工智能评估肺结节良恶性的基本过程、人工智能模型在鉴别肺结节良恶性方面效能、人工智能诊断肺结节效能的影响因素、问题及展望方面进行分析,以期提升人工智能辅助CT鉴别肺结节良恶性效果。Lung cancer is one of the common clinical malignant tumors. At present, chest CT is an important way to differentiate early lung cancer. However, because of its "different diseases with the same shadow" and the influence of clinical experience, there are significant differences in the differentiation of benign and malignant lesions, and it is easy to have misdiagnosis or missed diagnosis. In recent years, artificial intelligence has been gradually applied in clinical practice, which also plays a role in differentiating benign from malignant pulmonary tuberculosis. This article analyzes the basic process of artificial intelligence in evaluating benign and malignant pulmonary nodules, the efficacy of the artificial intelligence model in differentiating benign and malignant pulmonary nodules, and the influencing factors, problems and prospects of artificial intelligence in diagnosing pulmonary nodules, in order to improve the effect of artificial intelligence assisted CT in differentiating benign and malignant pulmonary nodules.
关 键 词:良恶性 肺结节 计算机断层扫描成像 人工智能 手动分割
分 类 号:R445[医药卫生—影像医学与核医学]
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