Porównaj metody

	Radiomika	Rekonstrukcja iteracyjna CT	DEXA (Absorpcjometria dwuenergetyczna)	Angiografia OCT
Dziedzina	Obrazowanie medyczne	Obrazowanie medyczne	Obrazowanie medyczne	Obrazowanie medyczne
Rodzina	Process / pipeline	Process / pipeline	Process / pipeline	Process / pipeline
Rok powstania	2012	1974	1987	2012
Twórca	Philippe Lambin	Richard Gordon	Harold Wahner	Yali Jia
Typ	Machine learning-based texture and morphology analysis	Algorithm for tomographic image reconstruction	X-ray-based bone density measurement	Optical imaging technique for vasculature visualization
Źródło pierwotne	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.	Gordon, R., Bender, R., Herman, G. T. (1974). Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography. Journal of Theoretical Biology, 29(3), 471-481.	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.	Jia, Y., Tan, O., Tokayer, J., et al. (2012). Split-spectrum amplitude-decorrelation angiography with optical coherence tomography. Optics Express, 20(4), 4710-4725.
Inne nazwy	texture analysis, radiomics analysis, quantitative imaging biomarkers	MBIR, ASIR, IR-CT, statistical reconstruction	Dual X-ray absorptiometry, DXA, bone densitometry	OCTA, OCT-A
Pokrewne	5	5	5	5
Podsumowanie	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.	CT Iterative Reconstruction (IR) is a computational technique that reconstructs tomographic images from raw X-ray projection data by iteratively refining an estimate of tissue attenuation until it matches the measured projections. Developed from algebraic reconstruction techniques pioneered by Gordon in 1974, iterative reconstruction has revolutionized clinical CT by enabling high-quality images at reduced radiation dose. Variants such as Adaptive Statistical Iterative Reconstruction (ASIR) and Model-Based Iterative Reconstruction (MBIR) are now standard on modern CT scanners.	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.	Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that visualizes the microvasculature in the retina and choroid by detecting motion contrast from flowing blood. Developed by Jia and colleagues in 2012, OCTA uses repeated OCT scans of the same tissue location to identify blood flow based on the decorrelation signal. It has become a critical diagnostic tool in ophthalmology for detecting retinal and macular diseases without requiring fluorescein injection.