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X-ray diffraction tomography with limited projection information.
Zhu, Zheyuan; Katsevich, Alexander; Kapadia, Anuj J; Greenberg, Joel A; Pang, Shuo.
Afiliación
  • Zhu Z; CREOL, The College of Optics and Photonics, University of Central Florida, Orlando, 32816, USA.
  • Katsevich A; Department of Mathematics, University of Central Florida, Orlando, 32816, USA.
  • Kapadia AJ; Department of Radiology, Duke University, Durham, 27705, USA.
  • Greenberg JA; Department of Electrical and Computer Engineering, Duke University, Durham, 27708, USA.
  • Pang S; CREOL, The College of Optics and Photonics, University of Central Florida, Orlando, 32816, USA. pang@creol.ucf.edu.
Sci Rep ; 8(1): 522, 2018 01 11.
Article en En | MEDLINE | ID: mdl-29323224
X-ray diffraction tomography (XDT) records the spatially-resolved X-ray diffraction profile of an extended object. Compared to conventional transmission-based tomography, XDT displays high intrinsic contrast among materials of similar electron density and improves the accuracy in material identification thanks to the molecular structural information carried by diffracted photons. However, due to the weak diffraction signal, a tomographic scan covering the entire object typically requires a synchrotron facility to make the acquisition time more manageable. Imaging applications in medical and industrial settings usually do not require the examination of the entire object. Therefore, a diffraction tomography modality covering only the region of interest (ROI) and subsequent image reconstruction techniques with truncated projections are highly desirable. Here we propose a table-top diffraction tomography system that can resolve the spatially-variant diffraction form factor from internal regions within extended samples. We demonstrate that the interior reconstruction maintains the material contrast while reducing the imaging time by 6 folds. The presented method could accelerate the acquisition of XDT and be applied in portable imaging applications with a reduced radiation dose.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos