A Model-Based Unsupervised Deep Learning Method for Low-Dose CT Reconstruction

A Model-Based Unsupervised Deep Learning Method for Low-Dose CT Reconstruction

Low-dose CT (LDCT) is of great significance due to the concern about the potential radiation risk. With the fast development of deep learning, neural networks have become powerful tools in LDCT enhancement. Current deep neural networks for LDCT reconstruction are often trained with paired LDCT datas...

Full description

Bibliographic Details
Main Authors: Kaichao Liang, Li Zhang, Hongkai Yang, Zhiqiang Chen, Yuxiang Xing
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Low-dose CT
deep learning
unsupervised learning
semi-supervised learning
Online Access:https://ieeexplore.ieee.org/document/9180342/

Internet

https://ieeexplore.ieee.org/document/9180342/

Similar Items