Robust sparse reconstruction for Cherenkov luminescence tomography based on look ahead orthogonal matching pursuit algorithm

Cherenkov luminescence tomography (CLT) has become a novel three-dimensional (3D) non-invasive technology for biomedical applications such as tumor detection, pharmacodynamics evaluation, etc. However, the reconstruction of CLT still remains a challenging task because of the strong absorbing effect and scattering effect of Cherenkov photon transport process. In this study, we proposed a novel robust sparse reconstruction method named look ahead orthogonal matching pursuit (LAOMP) algorithm to improve the robustness and accuracy of reconstruction for CLT instead of traditional OMP algorithm based on a look ahead strategy. To validate the reconstruction performance of LAOMP method, a series of numerical simulations were conducted. The results showed that LAOMP method obtained the higher robustness and accuracy in locating the optical sources compared with the OMP and StOMP algorithms.