FAST STATISTICAL IMAGING RECONSTRUCTION VIA DENOISED ORDERED-SUBSET STATISTICALLY-PENALIZED ALGEBRAIC RECONSTRUCTION TECHNIQUE

摘要

Described here are systems and methods for iteratively reconstructing images from data acquired using a medical imaging system. The image reconstruction is decomposed into separate linear sub-problems that can be more efficiently solved. A statistical image reconstruction process is decomposed into a statistically-weighted algebraic reconstruction update sequence. After this step, the reconstructed image is denoised using a regularization function.