| Recent Advances in Imaging Analysis for Interstitial Lung Disease |
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Ju Hyun Oh1, Jin Woo Song2 |
1Department of Pulmonary and Critical Care Medicine, Ajou University Hospital, Ajou University School of Medicine, Suwon, Korea
2Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea |
| 간질성 폐질환에서의 영상 분석 최신 기술 동향 |
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오주현1, 송진우2 |
1아주대학교 의과대학 아주대학교병원 호흡기내과
2울산대학교 의과대학 서울아산병원 호흡기내과 |
Correspondence:
Jin Woo Song, Tel: +82-2-3010-3993, Fax: +82-2-3010-6968, Email: jwsongasan@gmail.com
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Received: 30 June 2025 • Revised: 31 August 2025 • Accepted: 16 September 2025 |
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| Abstract |
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Interstitial lung disease (ILD) encompasses a heterogeneous group of pulmonary disorders with variable etiologies, clinical courses, and prognoses. Recent advances in imaging analysis, particularly automated quantification and artificial intelligence-based technologies, have significantly enhanced diagnostic precision and prognostic modeling. Quantitative high-resolution computed tomography allows objective assessment of disease extent, pattern classification, and regional distribution of fibrotic lesions, providing essential information for staging and treatment decisions. Deep-learning-based segmentation and pattern recognition techniques can extract high-dimensional imaging features, facilitating phenotype clustering, risk stratification, and longitudinal monitoring. Recent efforts to integrate imaging data with clinical parameters and multi-omics profiles have further advanced the field of precision medicine. This review discusses the current state of imaging analysis technologies for ILD, emphasizing clinical applications, disease-specific use cases, and emerging directions for biomarker discovery and individualized patient care. |
| Key Words:
Lung diseases, interstitial; Artificial intelligence; Diagnostic imaging; Radiographic image interpretation, computer-assisted; Prognosis |
| 주제어:
간질성 폐질환; 인공지능; 영상 분석; 정량화; 예후 |
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