CT Iterative Reconstruction
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.
원본 기록
방법의 원본 기록에서 그대로 복사된 인용입니다. 이로부터 수준별 검증이 추론되지 않습니다.
- 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. · URL
- Yu, L., Leng, S., McCollough, C. H. (2012). Iterative reconstruction in medical imaging. Journal of Medical Imaging, 1(3), 033506. · URL
- Singh, S., Kalra, M. K., Hsieh, J., et al. (2010). Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. Radiology, 257(2), 373-383. · DOI 10.1148/radiol.10092212
큐레이션된 주장
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관련 방법
방법 그래프에서 생성되었으며 기계가 제안한 관계로 표시됩니다 — 증거 주장이 추론되지 않습니다.