A fast reconstruction algorithm based on parallel coordinate descent optimization for in vivo tomographic bioluminescence imaging

Bioluminescence imaging (BLI) offers an alternative opportunity for non-invasively visualizing biological processes at the physiological and molecular levels in whole animals. Tomographic bioluminescence imaging (TBI) can further translate planar imaging into three-dimensional quantitative bioluminescent source distribution. Although many reconstruction methods have been developed, efforts are still needed to make the tomographic methods more practical for biomedical imaging experiments. In this paper, a fast reconstruction algorithm based on parallel coordinate descent optimization is proposed for in vivo tomographic bioluminescence imaging. Based on the shrinking operation, the proposed method is very efficient. Moreover, in order to obtain the analytic form of the updating shrinkage function, a smooth and convex approximation to the regularization term L_p is utilized, so this term can be easily generalized for 1 ≤ p ≤ 2. In the experiments, the imaging performance of the proposed method demonstrates that it has the ability to recover reliable tomographic results with a wide range of regularization parameters and different p. Moreover, the high efficiency makes it potential for real time imaging reconstruction.