Examinando por Materia "RECONSTRUCCIÓN DE IMÁGENES"

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    Image-quality optimization for dual energy computed tomography (DECT) three-material decomposition
    (2014-04-23) Arboleda-Clavijo, C. (Carolina); Pelc, N. (Norbert)
    Dual energy computed tomography, which consists of the acquisition of two images of a given region of interest using two different x-ray energies, has been used to decompose images. For example, it has been proposed to estimate the degree of stenosis of blood vessels with calcifi ed plaques. Pragmatic realities, though, such as beam hardening, scattered radiation and mostly quantum noise, reduce the ideal of a perfect decomposition. In this study, a dual energy separation method for iodinated contrast media, cortical bone and soft tissue was implemented; afterwards, it was tested in simulated noiseless and noisy situations. The noise propagation was modeled mathematically, and an image-quality optimization technique regarding the right distribution of radiation dose between the high and low energy images was proposed. The results obtained suggest that in the absence of noise and using mono-energetic beams, an accurate separation is possible, but when noise is added and poly-chromatic spectra used this decomposition becomes more challenging.
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    Tomografía computarizada por rayos X: fundamentos y actualidad
    (2014-04-23) Ramírez-Giraldo, J. C. (Juan Carlos); Arboleda-Clavijo, C. (Carolina); McCollough, C. (Cynthia)
    This paper reviews the fundamentals of x-ray computed tomography. It starts by summarizing the early days of the technique and its evolution through time, as well as the physical principles of x-ray production. Subsequently, the mathematical principles of image reconstruction are discussed with emphasis in both analytical and iterative reconstruction methods. A complete section is dedicated to review the main concepts related with the risks of ionizing radiation, and discuss some of the most recent controversies about CT radiation and how those risks affect scanning protocols. Finally, based on the most recent advances and trends in CT, the paper discuss about those areas, which, presumably, will be the research focus of CT in the near future.