Photon-counting Micro-CT Scanner MARS:

There are two Photon Counting CT(PCCT) scan machines available in CBIS 1343 and CBIS 1420: The MARS-16 machine and the MARS-19 machine.

The MARS-16 x-ray photon-counting preclinical scanner donated by MARS Bioimaging to our lab decomposes materials in a sample or a living animal during a single scan. It is the first commercially available spectral micro-CT system to produce images with anatomic, functional, and molecular quantification at a fraction of the cost and time of PET and SPECT. This scanner consists of Medpix3 detectors bonded to High-Z sensors at 110µm pitch, 8 energy bins and 2ms frame readout, an x-ray source at 120kVp and 350μA in circular and helical scan modes, a precision horizontal in vivo sample stage with gas lines, monitoring sensors, reconstruction algorithms, and a visualization workstation with an HP 3D VR display. Furthermore, through an NIH HEI grant (PI: Ge Wang) our CBIS / BIC has the latest system model MARS-20 installed in 2020 to serve local and regional users.

Figure: Image of the MARS-19 machine in CBIS.

Key Features

  • Upto 14 Scans in One Day
  • Shorter scan time
  • Improved reconstructed
  • MARS Material Decomposition algorithm.

Scanning Diversity:

  • Sacrificed mice
  • Live mice
  • Rats
  • Small rabbits
  • Phantoms and Solutions

Figure: Image of sacrifised mice scanning in MARS-19.

Adjacent Support:

  • Freezer facility in CBIS for sample storage
  • Surgery table in the MARS-19 room for convenience

Major Publications using MARS PCCT:

  • Li, Mengzhou, et al. “Motion correction for robot-based x-ray photon-counting CT at ultrahigh resolution.” Developments in X-Ray Tomography XIV. Vol. 12242. SPIE, 2022.
  • Li, Mengzhou, et al. “Motion Correction via Locally Linear Embedding for Helical Photon-counting CT.” arXiv preprint arXiv:2204.02490 (2022).
  • Evans, Connor J., et al. “Effects of image denoising on quantitative material decomposition in photon-counting spectral computed tomography.” Medical Imaging 2022: Physics of Medical Imaging. Vol. 12031. SPIE, 2022.
  • Getzin, Matthew, et al. “Non-uniformity correction for MARS photon-counting detectors.” 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. Vol. 11072. SPIE, 2019.
  • Li, Mengzhou, David S. Rundle, and Ge Wang. “X-ray photon-counting data correction through deep learning.” arXiv preprint arXiv:2007.03119 (2020).


We are actively collaborating with external researchers interested in Contrast Agents, Reconstruction, Material Decomposition and more.

For Collaboration

  • If you find our research and experimental setup interesting, do reach out! Prof. Ge Wang