방법 비교

	방사선체학(Radiomics)	정량적 감수성 맵핑
분야	의료영상	의료영상
계열	Process / pipeline	Process / pipeline
기원 연도	2012	2015
창시자	Philippe Lambin	Yong Wang
유형	Machine learning-based texture and morphology analysis	Quantitative MRI contrast mechanism
원전	Lambin, P., Rios-Velazquez, E., Leijenaar, R., et al. (2012). Radiomics: extracting more information from medical images using advanced feature analysis. Nature Reviews Clinical Oncology, 9(12), 676-684.	Wang, Y., Liu, T. (2015). Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker. Magnetic Resonance in Medicine, 73(1), 82-101.
별칭	texture analysis, radiomics analysis, quantitative imaging biomarkers	QSM, susceptibility-weighted imaging
관련	5	5
요약	Radiomics is a computational methodology that extracts large numbers of quantitative features from medical images (CT, MRI, PET) using automated image analysis and machine learning to discover imaging biomarkers associated with disease phenotype, prognosis, and treatment response. Developed by Lambin, Gillies, and colleagues in 2012, radiomics aims to decode the biology underlying visible imaging patterns, enabling personalized medicine through image-based phenotyping. It has emerged as a powerful tool in oncology for tumor characterization, prognosis prediction, and therapy response assessment.	Quantitative Susceptibility Mapping (QSM) is a post-processing technique that converts MRI phase data into quantitative susceptibility values, enabling direct visualization and measurement of tissue magnetic properties. Developed by Wang, Liu, and colleagues, QSM transforms phase shifts caused by differences in magnetic susceptibility between tissues into tissue-specific biomarkers. It has revolutionized the sensitivity of MRI to iron, calcium, and other paramagnetic and diamagnetic substances, making it valuable in neurodegenerative disease diagnosis and tissue characterization.