摘要间质性肺疾病（ILD）的精确诊断依赖于高分辨率计算机体层成像，但传统的视觉分析方式存在明显的主观性。主要介绍了基于人工智能的定量计算机体层成像（CT）分析软件在评价ILD中的研究进展，包括CALIPER、自适应多特征法、数据驱动纹理分析、定量肺纤维化/定量ILD、系统目标纤维化影像分析算法、e-Lung、呼吸功能成像、AirQuant、Fibresolve和3D Slicer 10种主流定量CT分析软件的核心技术框架、临床应用场景、数据采集标准、技术优势和应用局限，同时分析了这些软件的合理选择策略，并总结了其目前存在的挑战和发展前景。

abstractsAccurate diagnosis of interstitial lung disease (ILD) depends on high resolution computed tomography, but traditional visual analysis is limited by subjectivity. In this review, the research progress of artificial intelligence-based quantitative computed tomography (CT) analysis software for evaluating ILD was mainly introduced. The core technical framework, clinical application scenarios, data acquisition standards, technical advantages and application limitations of ten mainstream quantitative CT analysis software packages were analyzed, including CALIPER, the adaptive multiple feature method, data-driven texture analysis, quantitative lung fibrosis/quantitative ILD, the systematic objective fibrotic imaging analysis algorithm, e-Lung, functional respiratory imaging, AirQuant, Fibresolve and 3D Slicer. The reasonable selection strategies for these software programs were also analyzed, as were the existing challenges and development prospects.