Research progress of artificial intelligence-based quantitative CT analysis software in the evaluation of interstitial lung disease
10.3760/cma.j.cn121382-20250605-00042
- VernacularTitle:基于人工智能的定量CT分析软件在评价间质性肺疾病中的研究进展
- Author:
Long LI
1
;
Qianglin HAN
Author Information
1. 广州医科大学附属市十二人民医院放射科，广州 510620
- Keywords:
Artificial intelligence;
Interstitial lung disease;
Computed tomography;
Adaptive multiple feature method;
Data-driven texture analysis;
Systematic objecti
- From:
International Journal of Biomedical Engineering
2025;48(4):413-422
- CountryChina
- Language:Chinese
-
Abstract:
Accurate 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.
