Auto-tuned Path-based Iterative Reconstruction (aPBIR) for X-ray Computed Tomography

Model-based iterative reconstruction (MBIR) techniques have demonstrated many advantages in X-ray CT image reconstruction. The tuning parameter value in MBIR that regulates the strength of the penalty function is critical for achieving good reconstruction results but difficult to choose. The path-based iterative reconstruction (PBIR) method empowered by the path seeking algorithm is capable of efficiently generating a series of MBIR images with different strengths of the penalty function. In this paper, we present an approach to automatically select the tuning parameter value by finding the maximal separation between the noise reduction and the smoothing effects. Simulations shows that the proposed auto-tuned PBIR method produces images that are comparable to the hypothetically ”best” MBIR image.