Dose reduction potential of vendor-agnostic deep learning model in comparison with deep learning–based image reconstruction algorithm on CT: a phantom study

被引：0
|
作者：
Hyunsu Choi
Won Chang
Jong Hyo Kim
Chulkyun Ahn
Heejin Lee
Hae Young Kim
Jungheum Cho
Yoon Jin Lee
Young Hoon Kim
机构：
[1] Seoul National University Bundang Hospital,Department of Radiology
[2] Seoul National University College of Medicine,Department of Radiology
[3] and Institute of Radiation Medicine,Department of Transdisciplinary Studies, Program in Biomedical Radiation Sciences, Graduate School of Convergence Science and Technology
[4] Seoul National University Medical Research Center,Department of Applied bioengineering, Graduate School of Convergence Science and Technology
[5] Seoul National University,undefined
[6] Seoul National University,undefined
来源：
European Radiology | 2022年 / 32卷
关键词：
Deep learning; Tomography, x-ray computed; Phantoms, imaging; Radiation dosage; Artificial intelligence;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：1247 / 1255
页数：8
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