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    Simulation and Modeling for UHR-MDCT and Photon-Counting CT

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    TAI-THESIS-2022.pdf (11.19Mb)
    Date
    2022-12-08
    Author
    Tai, Wei Yang
    0000-0001-5486-4486
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    Abstract
    New CT technologies, such as ultra-high resolution multi-detector CT (UHR-MDCT), and photon-counting CT, open the potential for visualizing bone microarchitecture and enables material decomposition with a single scan. UHR-MDCT comes with many challenges – image quality varies with the position of the object in the field-of-view. Visualizing trabecular structures and quantifying bone health using biomarkers becomes a difficult task under in the presence of radial, azimuthal, and longitudinal blur. PCCT, being the talk of the show in 2022, boasts superior image resolution and noise properties. This new technology, however, is unable to escape from scatter. The problem becomes compounded due to the availability of energy channels. Scatter distribution behaves differently in different energy channels and varies depending on object composition and position. Applications of PCCT, namely, material decomposition, become inaccurate in the presence of scatter. Software simulation for UHR-MDCT was created to study the extent of the non-stationary blurring effect caused by detector integration time and focal spot size. Quantifying the extent of image blurring will help optimize the application of trabecular metrics from UHR-MDCT to assess bone health. The distribution of scatter in energy channels for PCCT was investigated through Monte-Carlo scatter simulations in phase space. Scatter in energy channels were qualitatively and quantitatively assessed for phantoms of various bone and water compositions. Material decomposition for two basis materials: bone and water were performed in projection domain and the bias of estimated line integrals in the presence of single channel scatter were assessed. This scatter study enables improvements in the accuracy of tissue composition and contrast agent quantification in PCCT.
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    http://jhir.library.jhu.edu/handle/1774.2/68045
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