Comparer des méthodes

	Radiomique	Cartographie Quantitative de Susceptibilité
Domaine	Imagerie médicale	Imagerie médicale
Famille	Process / pipeline	Process / pipeline
Année d'origine	2012	2015
Auteur d'origine	Philippe Lambin	Yong Wang
Type	Machine learning-based texture and morphology analysis	Quantitative MRI contrast mechanism
Source fondatrice	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.
Alias	texture analysis, radiomics analysis, quantitative imaging biomarkers	QSM, susceptibility-weighted imaging
Apparentées	5	5
Résumé	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.