Mixed Confidence Estimation for Iterative CT Reconstruction.

Abstract

We present a statistical analysis of our previously proposed Constrain-Static Target-Kinetic algorithm for 4D CT reconstruction. This method, where framed iterative reconstruction is only performed on the dynamic regions of each frame, while static regions are fixed across frames to a composite image, was proposed to reduce computation time. In this work, we generalize the previous method to describe any application where a portion of the image is known with higher confidence (static, composite, lower-frequency content, etc.) and a portion of the image is known with lower confidence (dynamic, targeted, etc). We show that by splitting the image space into higher and lower confidence components, CSTK can lower the estimator variance in both regions compared to conventional reconstruction. We present a theoretical argument for this reduction in estimator variance and verify this argument with proof-of-principle simulations. This method allows for reduced computation time and improved image quality for imaging scenarios where portions of the image are known with more certainty than others.