【摘要】 尘肺病是全球范围内危害严重的一类职业病，早期影像学检查是诊断和防治尘肺病的重要手段之一。近年来，随着人工智能技术的快速发展，其在尘肺病影像诊断中的应用研究取得了显著进展。本文综述了数字化X线摄影（DR）、计算机断层扫描（CT）在尘肺病筛查诊断中的应用现状，重点阐述了人工智能技术在尘肺病影像诊断领域的研究进展，包括传统机器学习算法、深度学习网络模型的应用，以及基于人工智能的早期尘肺病影像学筛查新技术。同时，分析了当前研究中存在的问题和挑战，并对未来研究方向进行了展望。更多还原

【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.更多还原