Cerenkov luminescence tomography based on preconditioning orthogonal matching pursuit

20 March 2015 Cerenkov luminescence tomography based on preconditioning orthogonal matching pursuit

Haixiao Liu, Zhenhua Hu, Kun Wang, Jie Tian, Xin Yang

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Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94131X (2015) https://doi.org/10.1117/12.2081921
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Cerenkov luminescence imaging (CLI) is a novel optical imaging method and has been proved to be a potential substitute of the traditional radionuclide imaging such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). This imaging method inherits the high sensitivity of nuclear medicine and low cost of optical molecular imaging. To obtain the depth information of the radioactive isotope, Cerenkov luminescence tomography (CLT) is established and the 3D distribution of the isotope is reconstructed. However, because of the strong absorption and scatter, the reconstruction of the CLT sources is always converted to an ill-posed linear system which is hard to be solved. In this work, the sparse nature of the light source was taken into account and the preconditioning orthogonal matching pursuit (POMP) method was established to effectively reduce the ill-posedness and obtain better reconstruction accuracy. To prove the accuracy and speed of this algorithm, a heterogeneous numerical phantom experiment and an in vivo mouse experiment were conducted. Both the simulation result and the mouse experiment showed that our reconstruction method can provide more accurate reconstruction result compared with the traditional Tikhonov regularization method and the ordinary orthogonal matching pursuit (OMP) method. Our reconstruction method will provide technical support for the biological application for Cerenkov luminescence.

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Haixiao Liu, Zhenhua Hu, Kun Wang, Jie Tian, and Xin Yang "Cerenkov luminescence tomography based on preconditioning orthogonal matching pursuit", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94131X (20 March 2015); https://doi.org/10.1117/12.2081921

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