Information theoretic discrepancy based iterative reconstruction for transmission tomography

The monochromatic approximation, which postulates that a source emits monochromatic radiation, has been widely used in the transmission tomography. However, due to the ignorance of energy dependency, image degradations such as beam hardening artifact are often occurred. In this paper, we present novel reconstruction algorithms to reflect the exact polychromatic model. Departing from the conventional algebraic and statistical reconstructions, the generalized information theoretic discrepancy (GID) is employed as the new data fidelity metric. By using the particular features of the GID, the cost function is derived in terms of imaginary variables, which incorporates energy dependency and leads to a tractable optimization problem even without the monochromatic approximation. In preliminary experiments with a simulated dual energy CT and a real experimental tomosyn-thesis, the proposed information theoretic discrepancy based iterative reconstruction (IDIR) algorithm showed superior performances over conventional reconstruction schemes.