2D diffuse optical imaging using clustered sparsity

Diffuse optical imaging (DOI) is a non-invasive technique which measures hemodynamic changes in the tissue with near infrared light, and has been increasingly used to study brain functions. Due to the nature of light propagation in the tissue, the reconstruction problem is severely ill-posed. Sparsity-regularization has achieved promising results in recent works for linearized DOI problem. In this paper, we exploit more prior information to improve DOI besides sparsity. Based on the functional specialization of the brain, the in vivo absorption changes caused by specific brain function can be clustered in certain region(s) and not randomly distributed. Thus, a new algorithm is proposed to utilize this prior in reconstruction. Results of numerical simulations and phantom experiments have demonstrated the superiority of the proposed method over the state-of-the-art.