Affiliations: The Key Lab of Optoelectronic Technology and Systems
of the Education Ministry of China, Chongqing University, Chongqing,
China | Biomedical Imaging Division, VT-WFU School of
Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, VA, USA | Department of Radiology, Division of Radiologic
Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA | Biomedical Imaging Division, VT-WFU School of
Biomedical Engineering and Sciences, Wake Forest University Health Sciences,
Winston-Salem, NC, USA | Department of Radiology, University of Otago,
Christchurch, New Zealand | Department of Physics and Astronomy, University of
Canterbury, Christchurch, New Zealand | European Organization for Nuclear Research, Geneva,
Switzerland
Note: [] Corresponding authors: Hengyong Yu, Ge Wang, Biomedical Imaging
Division, VT-WFU School of Biomedical Engineering and Sciences, Virginia Tech,
Blacksburg, VA 24061, USA. E-mail: [email protected]; [email protected]
Abstract: Experiments were performed to evaluate the energy-discriminative
performance of a spectral (multi-energy) micro-CT system. The system, designed
by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New
Zealand), employs a photon-counting energy-discriminative detector technology
developed by CERN (European Organization for Nuclear Research). We used the
K-edge attenuation characteristics of some known materials to calibrate the
detector's photon energy discrimination. For tomographic analysis, we used the
compressed sensing (CS) based ordered-subset simultaneous algebraic
reconstruction techniques (OS-SART) to reconstruct sample images, which is
effective to reduce noise and suppress artifacts. Unlike conventional CT, the
principal component analysis (PCA) method can be applied to extract and
quantify additional attenuation information from a spectral CT dataset. Our
results show that the spectral CT has a good energy-discriminative performance
and provides more attenuation information than the conventional CT.
