Deep Learning Image Reconstruction to Improve Computed Tomography Image Quality of the Phantom with Standard Liver Density

Deep Learning Image Reconstruction to Improve Computed Tomography Image Quality of the Phantom with Standard Liver Density

Objective: This study aimed to compare the quality of reconstructed images by deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-V (ASIR-V) techniques at different scan doses using a phantom with liver density. Methods: The Gammex computed tomography (CT) pha...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhijie PAN, Ling LIU, Qingyao LI, Tingting QU, Shuai ZHANG, Xueqian XIE
Format: Article
Language:English
Published: Editorial Office of Computerized Tomography Theory and Application 2025-07-01
Series:CT Lilun yu yingyong yanjiu
Subjects:
deep learning
phantom
ct
radiation dose
Online Access:https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2024.056
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items