方法证据记录
Radiomics
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Quantitative Radiomics
分类方法记录 · process-pipeline / medical-imaging
- 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. · DOI 10.1016/j.ejca.2011.11.036
- Gillies, R. J., Kinahan, P. E., Hricak, H. (2016). Radiomics: images are data. Radiology, 278(2), 563-577. · URL
- Kumar, V., Gu, Y., Basu, S., et al. (2012). Radiomics: the process and the challenges. Magnetic Resonance Imaging, 30(9), 1234-1248. · DOI 10.1016/j.mri.2012.06.010
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