Deep iterative reconstruction estimation (DIRE): approximate iterative reconstruction estimation for low dose CT imaging.

Deep iterative reconstruction estimation (DIRE): approximate iterative reconstruction estimation for low dose CT imaging.
Phys Med Biol. 2019 Apr 12;:
Authors: Liu J, Zhang Y, Zhao Q, Lv T, Wu W, Cai N, Quan G, Yang W, Chen Y, Luo L, Shu H, Coatrieux JL
Abstract
The image quality in low dose computed tomography (LDCT) can be severely degraded by amplified mottle noise and streak artifacts. Although the iterative reconstruction (IR) algorithms bring sound improvements, their high computation cost remains a major inconvenient. In this work, a deep iterative reconstruction estimation (DIRE) strategy is developed to estimate IR images from LDCT analytic reconstructions images. Within this DIRE strategy, a 3D residual convolutional network (3D ResNet) architecture is proposed. Experiments on several simulated and real datasets as well as comparisons with state-of-the-art methods demonstrate that the proposed approach is effective in providing improved LDCT images.
PMID: 30978718 [PubMed - as supplied by publisher]

Source: Physics in Medicine and Biology - April 11, 2019 Category: Physics Authors: Liu J, Zhang Y, Zhao Q, Lv T, Wu W, Cai N, Quan G, Yang W, Chen Y, Luo L, Shu H, Coatrieux JL Tags: Phys Med Biol Source Type: research