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人工智能医学影像辅助诊断系统在肺结节诊断中的应用

Application of artificial intelligence medical imaging aided diagnosis system in the diagnosis of pulmonary nodules.

作者信息

Yang Ya, Wang Pan, Yu Chengzhou, Zhu Jing, Sheng Jinping

机构信息

Department of Radiology, Chinese People's Liberation Army The General Hospital of Western Theater Command, No. 270, Tianhui Road, Rongdu Avenue, Jinniu District, Chengdu, Sichuan, 610083, China.

Chinese People's Liberation Army Marine Corps Hospital, Chaozhou, Guangdong, 521000, China.

出版信息

BMC Med Inform Decis Mak. 2025 May 14;25(1):185. doi: 10.1186/s12911-025-03009-4.

Abstract

The application of artificial intelligence (AI) technology has realized the transformation of people's production and lifestyle, and also promoted the rapid development of the medical field. At present, the application of intelligence in the medical field is increasing. Using its advanced methods and technologies of AI, this paper aims to realize the integration of medical imaging-aided diagnosis system and AI, which is helpful to analyze and solve the loopholes and errors of traditional artificial diagnosis in the diagnosis of pulmonary nodules. Drawing on the principles and rules of image segmentation methods, the construction and optimization of a medical image-aided diagnosis system is carried out to realize the precision of the diagnosis system in the diagnosis of pulmonary nodules. In the diagnosis of pulmonary nodules carried out by traditional artificial and medical imaging-assisted diagnosis systems, 231 nodules with pathology or no change in follow-up for more than two years were also tested in 200 cases. The results showed that the AI software detected a total of 881 true nodules with a sensitivity of 99.10% (881/889). The radiologists detected 385 true nodules with a sensitivity of 43.31% (385/889). The sensitivity of AI software in detecting non-calcified nodules was significantly higher than that of radiologists (99.01% vs 43.30%, P < 0.001), and the difference was statistically significant.

摘要

人工智能(AI)技术的应用实现了人们生产生活方式的转变,也推动了医学领域的快速发展。目前,智能技术在医学领域的应用日益增多。本文利用AI先进的方法和技术,旨在实现医学影像辅助诊断系统与AI的融合,有助于分析和解决传统人工诊断在肺结节诊断中的漏洞和误差。借鉴图像分割方法的原理和规则,开展医学图像辅助诊断系统的构建与优化,以实现诊断系统在肺结节诊断中的精准性。在传统人工和医学影像辅助诊断系统对肺结节的诊断中,还对200例中有病理结果或随访两年以上无变化的231个结节进行了检测。结果显示,AI软件共检测出881个真阳性结节,敏感度为99.10%(881/889)。放射科医生检测出385个真阳性结节,敏感度为43.31%(385/889)。AI软件检测非钙化结节的敏感度显著高于放射科医生(99.01%对43.30%,P < 0.001),差异具有统计学意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d39/12080151/6d94dff4de44/12911_2025_3009_Fig1_HTML.jpg

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