Linganisha mbinu

	Radiomics	DEXA
Nyanja	Upigaji Picha za Kitiba	Upigaji Picha za Kitiba
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2012	1987
Mwanzilishi	Philippe Lambin	Harold Wahner
Aina	Machine learning-based texture and morphology analysis	X-ray-based bone density measurement
Chanzo asilia	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.	Kanis, J. A. (1994). Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. World Health Organization Technical Report Series, 843, 1-129.
Majina mbadala	texture analysis, radiomics analysis, quantitative imaging biomarkers	Dual X-ray absorptiometry, DXA, bone densitometry
Zinazohusiana	5	5
Muhtasari	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.	Dual-Energy X-ray Absorptiometry (DEXA or DXA) is a non-invasive imaging technique that quantifies bone mineral density (BMD) by measuring the attenuation of X-rays at two different energies as they pass through bone and soft tissue. First developed by Wahner and colleagues in 1987, DEXA has become the gold standard for osteoporosis screening and fracture risk assessment. It is recommended by the World Health Organization for diagnosing osteoporosis and monitoring treatment response.