Abstract—x-ray Micro-ct Is an Important Imaging Tool for Biomedical Researchers. Our Group Recently Proposed a Hybrid 'true-color' Micro-ct System to Improve Contrast Resolution with Lower System Cost and Radiation Dose. the System Incorporates an Energy-resolved Photon-counting True-color Detector

X-ray micro-CT is an important imaging tool for biomedical researchers. Our group recently proposed a hybrid ‘true-color’ micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a “color diffusion” phenomenon was observed whereby high quality true-color images are produced not only inside the region of interest (ROI), but also in neighboring Manuscript received December 31, 2011. This work was supported in part by NIH/NIBIB grant EB011785 and a seed grant from Wake Forest Institute for Regenerative Medicine. Qiong Xu is with the Institute of Image Processing and Pattern Recognition, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China & the Department of Radiology, Division of Radiologic Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA. Hengyong Yu and Ge Wang are with the Department of Radiology, Division of Radiologic Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA & Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, 27157, USA & Virginia Tech, Blacksburg, VA 24061, USA. (e-mail: Hengyong-yu@ieee.org, ge-wang@ieee.org). James Bennett, Peng He and Haiou Shen are with Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Virginia Tech, Blacksburg, VA 24061, USA. Rafidah Zainon, Robert Doesburg and Alex Opie are with the Department of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. Mike Walsh is with the Department of Radiology, University of Otago, P.O. Box 4345 Christchurch, New Zealand. Anthony Butler is with the Department of Radiology, University of Otago, P.O. Box 4345 Christchurch, New Zealand & the European Organization for Nuclear Research (CERN), Geneva, Switzerland. Phillip Butler is with the Department of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand & the European Organization for Nuclear Research (CERN), Geneva, Switzerland. Xuanqin Mou is with the Institute of Image Processing and Pattern Recognition, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China regions. It appears harnessing this phenomena could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose.