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人工智能在结核病影像诊断中应用的研究进展

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结核病作为主要经呼吸道传播的慢性传染病,目前关于结核病的防治难点之一依然是诊断问题.早期、准确、灵敏发现结核病灶对患者有极大的益处.目前,结核病的诊断主要基于对患者症状和体征、实验室检查和胸部影像的综合考虑.其中,影像学检查在支持结核病早期诊断尤其是用于结核病筛查和鉴别诊断方面,发挥着关键作用.近年来,随着计算机技术的快速发展,人工智能(AI)已经广泛应用于医疗领域的各个方面,且持续的技术进步正在促进AI在影像诊断中的广泛使用.其中,AI与大量医学图像的积累相结合,为在医学应用中建立计算机辅助检测系统提供了新的机遇,越来越多的研究体现出AI辅助影像诊断技术在结核病影像诊断中的价值.本文对AI辅助影像诊断技术在结核病发现中的研究和应用进展进行综述.
Research and application progress of artificial intelligence-assisted imaging diagnosis in tuberculosis prevention and control
Tuberculosis is a chronic infectious disease mainly transmitted through the respiratory tract.At present,diag-nosis is still one of the difficulties in the prevention and treatment of tuberculosis.Early,accurate and sensitive detection of tuberculosis focus is of great benefit to patients.The diagnosis of tuberculosis is mainly based on the comprehensive con-sideration of patients'symptoms and signs,laboratory tests and chest images currently.Among them,imaging examination plays a key role in supporting early diagnosis of tuberculosis,especially in screening and differential diagnosis of tuberculo-sis.In recent years,with the rapid development of computer technology,artificial intelligence(AI)has been widely applied in various aspects of the medical field,and continuous technological progress is promoting the widespread use of AI in ima-ging diagnosis.The combination of AI and the accumulation of a large number of medical images provides a new opportuni-ty for the establishment of computer aided detection systems in medical applications.More and more research reflects the value of AI assisted image diagnosis technology in the image diagnosis of tuberculosis.This article reviews the research and application progress of AI assisted imaging diagnosis in the detection of tuberculosis.

TuberculosisMycobacterium tuberculosisDiagnostic imagingArtificial intelligence(AI)Auxiliary imaging diagnosis

刘梦晗、刘宇红、李亮

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山东大学齐鲁医学院公共卫生学院流行病学系,山东济南 250012

首都医科大学附属北京胸科医院(北京市结核病胸部肿瘤研究所)中国疾病预防控制中心结核病防治临床中心

首都医科大学附属北京胸科医院(北京市结核病胸部肿瘤研究所)

结核病 结核分枝杆菌 影像诊断 人工智能 辅助影像诊断

北京市卫生健康委高层次公共卫生技术人才建设项目

学科带头人-01-11

2024

预防医学论坛
中华预防医学会

预防医学论坛

影响因子:0.645
ISSN:1672-9153
年,卷(期):2024.30(3)
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