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12 March 2018 Dynamic cone beam x-ray luminescence computed tomography with principal component analysis
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Cone beam X-ray luminescence computed tomography (CB-XLCT) has recently been proposed as a new molecular imaging modality for various biomedical applications. It utilizes X-ray excitable nanophosphors to produce visible or near-infrared (NIR) luminescence and combines the high sensitivity of optical imaging with the high spatial resolution of X-ray imaging. With the development of the nanophosphors and reconstruction methods, dynamic XLCT imaging, which can reflect the dynamic course of absorption, distribution, and elimination of the nanophosphors in vivo, has demonstrated its initial prospect in biological and biochemical studies. However, challenges remain in resolving nanophosphors (drug) distributions inside the imaging object due to the high light scattering and complex dynamics of nanophosphor’s delivery. Considering that target with different functions may have different kinetic behaviors, in this paper we present a method to resolve targets with different kinetics by utilizing principal component analysis (PCA). The metabolic processes of nanophosphors (Y2O3:Eu3+) of two targets were simulated and imaged using a CB-XLCT system, with two targets located at different edge-to-edge distances of 0.12 cm. Simulation and experiment studies validate the performance of the proposed algorithm. The results suggest that two adjacent targets of different kinetic behaviors can be extracted and illustrated by the proposed method, at an edge-to-edge distance of 0.12 cm.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peng Gao, Junyan Rong, Tianshuai Liu, Wenli Zhang, Huangsheng Pu, Yuanke Zhang, and Hongbing Lu "Dynamic cone beam x-ray luminescence computed tomography with principal component analysis", Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 105780Z (12 March 2018);

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