Principles of Deep Learning Reconstruction Algorithm and Its Clinical Application Progress in Abdominal CT
10.3969/j.issn.1005-5185.2025.01.019
- VernacularTitle:深度学习重建算法的原理及其在腹部CT临床应用进展
- Author:
Yuncheng LI
1
;
Wei DENG
1
;
Xiaohu LI
1
Author Information
1. 安徽医科大学第一附属医院放射科,安徽 合肥 230022
- Publication Type:Journal Article
- Keywords:
Tomography,X-ray computed;
Deep learning;
Image reconstruction algorithm;
Abdomen;
Review
- From:
Chinese Journal of Medical Imaging
2025;33(1):102-106
- CountryChina
- Language:Chinese
-
Abstract:
The deep learning reconstruction(DLR)algorithm is a new CT image reconstruction technology in recent years,which can be used as an alternative to filtered back projection and iterative reconstruction in clinical practice.Compared with traditional image reconstruction algorithms,the DLR algorithm can reduce image noise and radiation dose while preserving image texture,shortening reconstruction time,and improving diagnostic efficiency.Therefore,it has broad clinical application prospects in the field of image reconstruction.This article summarizes the basic principles of the DLR algorithm and its new progress in the clinical application of abdominal CT.
