人工智能在尘肺病数字胸片诊断中的应用进展

Application of artificial intelligence in digital chest radiography diagnosis of pneumoconiosis

尘肺病是目前我国负担最重的职业病,其诊断主要依靠人工阅读X射线高千伏或数字化摄影胸片,存在效率低、主观性强、对临界病变无法准确判断等问题。随着机器辅助诊断技术的进步,人工智能诊断技术高效、客观、量化等特点恰好解决上述缺点。本文对目前应用人工智能技术尤其是深度学习模型进行尘肺病数字胸片诊断的研究进展进行综述,并结合常规人工读片局限性,以阐明人工智能技术在尘肺病数字胸片诊断中的应用前景,为未来该领域研究提供方向。

Pneumoconiosis is the occupational disease with the highest burden in China currently.The diagnosis of pneumoconiosis mainly relies on manual reading of X-ray high-kilovoltage or digital photography chest radiograph,which has some problems such as low efficiency,strong subjectivity,and cannot accurately judge the critical lesions.With the progress of machine-aided diagnosis technology,the efficient,objective and quantitative of artificial intelligence diagnosis technology just solve the shortcomings above.This paper reviews the research progress in digital chest radiography diagnosis of pneumoconiosis using artificial intelligence technology,especially deep learning model,combined with the limitations of conventional manual reading,in order to clarify the application prospect of artificial intelligence technology in the diagnosis of pneumoconiosis by digital chest radiography,and provide a direction for future research in this field.