人工智能技术辅助尘肺病影像诊断的现状及未来

中图分类号：R135.2

文献标识码：A

DOI：10.3969/j.issn.1006-1959.2026.09.031

文章编号：1006-1959（2026）09-0173-05

Present Situation and Future of Artificial Intelligence Technology Assisted Imaging Diagnosis of Pneumoconiosis

WANG Ying， CHEN Hai， DAI Qi， CHEN Bin

（Department of Radiology， Ningbo No.2 Hospital， Ningbo 315010， Zhejiang， China）

Abstract： Pneumoconiosis is a serious occupational disease worldwide. Early imaging examination is one of the important means of diagnosis and prevention of pneumoconiosis. In recent years， with the rapid development of artificial intelligence technology， its application in the imaging diagnosis of pneumoconiosis has made significant progress. This paper reviews the application status of digital X-ray photography （DR） and computed tomography （CT） in the screening and diagnosis of pneumoconiosis， and focuses on the research progress of artificial intelligence technology in the field of pneumoconiosis imaging diagnosis， including the application of traditional machine learning algorithms， deep learning network models， and new technologies for early pneumoconiosis imaging screening based on artificial intelligence. At the same time， the problems and challenges in the current research are analyzed， and the future research direction is prospected.

Key words： Pneumoconiosis; Imaging diagnosis; Artificial intelligence; Machine learning; Deep learning; Computer-aided diagnosis

尘肺病是生产活动中持续吸入生产性粉尘而引起的一系列肺部疾病的总称，主要包括煤工尘肺、矽肺、石棉肺等，是中国乃至全球危害严重的一类职业病[1，2]。（剩余12025字）