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Deep learning super-resolution for dental CBCT using micro-CT reference and edge loss function

delete2025-11-02
delete0
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OA
AI
P
Pan Chen
B
Bowen Shen
Y
Yan Yang
吴
吴薇薇 (Weiwei Wu)
S
Surong Chen
G
Gengyu Zhou
T
T. Malik
S
Sajitha Kalathingal
J
Jingyu Hu *
F
Franklin R. Tay *
J
Jingzhi Ma *
DOI：10.1016/j.jdent.2025.106209delete
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摘要

摘要

En 中文
锥形束计算机断层扫描（CBCT）在牙科实践中得到广泛应用，但其空间分辨率有限，难以清晰显示精细的根管结构。微计算机断层扫描（micro-CT）虽具有更高的分辨率，但不适用于临床。本研究探讨了通过基于深度学习的超分辨率技术提升CBCT分辨率的可行性，并使用配对的micro-CT图像作为真实参考标准。
Keyword:
CBCT
deep learning
edge-loss
micro-CT
super-resolution
AI总结

AI总结

对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Journal of Dentistry 封面图
Journal of Dentistry
IF:
5.5
论文数:
1.4K
被引数:
1.7W

机构

A
Augusta University
学者数:
5.9K
论文数: 4.6K
被引数: 8.2K
H
huazhong university of science and technology
学者数:
2.7W
论文数: 8.1K
被引数: 5
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