Ontology highlight
ABSTRACT:
SUBMITTER: Liu P
PROVIDER: S-EPMC10365089 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Liu Peng P Xu Linsong L Fullerton Garrett G Xiao Yao Y Nguyen James-Bond JB Li Zhongyu Z Barreto Izabella I Olguin Catherine C Fang Ruogu R
Frontiers in radiology 20220525
A body of studies has proposed to obtain high-quality images from low-dose and noisy Computed Tomography (CT) scans for radiation reduction. However, these studies are designed for population-level data without considering the variation in CT devices and individuals, limiting the current approaches' performance, especially for ultra-low-dose CT imaging. Here, we proposed PIMA-CT, a physical anthropomorphic phantom model integrating an unsupervised learning framework, using a novel deep learning ...[more]