Adaptive scatter kernel deconvolution modeling for cone‐beam CT scatter correction via deep reinforcement learning

Abstract

In this paper, we propose an intelligent scatter correction framework that integrates the physical scatter kernel model with DRL algorithm, which has the potential to improve the accuracy of the clinical scatter correction method to obtain better CBCT imaging quality.