Tomographic bioluminescence imaging reconstruction via a dynamically sparse regularized global method in mouse models

摘要

Abstract. Generally, the performance of tomographic bioluminescence imaging is dependent on several factors,nsuch as regularization parameters and initial guess of source distribution. In this paper, a global-inexact-Newtonnbased reconstruction method, which is regularized by a dynamic sparse term, is presented for tomographicnreconstruction. The proposed method can enhance higher imaging reliability and efficiency. In vivo mousenexperimental reconstructions were performed to validate the proposed method. Reconstruction comparisons ofnthe proposed method with other methods demonstrate the applicability on an entire region. Moreover, the reliablenperformance on awide range of regularization parameters and initial unknown valueswere also investigated. Basednon the in vivo experiment and amouse atlas, the tolerance for optical propertymismatchwas evaluatedwith opticalnoverestimation and underestimation. Additionally, the reconstruction efficiency was also investigated with differentnsizes of mouse grids. We showed that this method was reliable for tomographic bioluminescence imaging innpractical mouse experimental applications. C u00022011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3570828]