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Superfast Scan of Focused X-Ray Luminescence Computed Tomography Imaging.
Fang, Yile; Zhang, Yibing; Lun, Michael C; Li, Changqing.
Afiliação
  • Fang Y; Department of Bioengineering, University of California, Merced, Merced, CA 95343, USA.
  • Zhang Y; Department of Bioengineering, University of California, Merced, Merced, CA 95343, USA.
  • Lun MC; Department of Bioengineering, University of California, Merced, Merced, CA 95343, USA.
  • Li C; Department of Electrical Engineering, University of California, Merced, Merced, CA 95343, USA.
IEEE Access ; 11: 134183-134190, 2023.
Article em En | MEDLINE | ID: mdl-38919730
ABSTRACT
X-ray luminescence computed tomography (XLCT) is a hybrid molecular imaging modality having the high spatial resolution of x-ray imaging and high measurement sensitivity of optical imaging. Narrow x-ray beam based XLCT imaging has shown promise for high spatial resolution imaging of luminescent targets in deep tissues, but the slow acquisition speed limits its applications. In this work, we have introduced a superfast XLCT scan scheme based on the photon counter detector and a fly-scanning method. The new scan scheme is compared with three other scan methods. We have also designed and built a single-pixel x-ray detector to detect object boundaries automatically. With the detector, we can perform the parallel beam CT imaging with the XLCT imaging simultaneously. We have built the prototype XLCT imaging system to verify the proposed scan scheme. A phantom embedded with a set of four side-by-side cylindrical targets was scanned. With the proposed superfast scan scheme, we have achieved 43 seconds per transverse scan, which is 28.6 times faster than before with slightly better XLCT image quality. The superfast scan allows us to perform 3D pencil beam XLCT imaging in the future.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article