Sparse2Noise:低剂量同步龙X射线断层扫描,没有高质量的参考数据
Xiaoman Duan1, Xiao Fan Ding1, Naitao Li1
1Division of Biomedical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
Computers in biology and medicine
|September 10, 2023
概括
Sparse2Noise是一种新的低剂量成像策略,用于同步辐射计算机断层扫描 (SR-CT). 这种方法有效地减少噪音和人工物,使得在较低的辐射剂量下能够进行高质量的体内成像.
科学领域:
- 医疗成像医学成像
- 生物医学工程 生物医学工程
- 放射学 放射学是一门学科.
背景情况:
- 同步射计算断层扫描 (SR-CT) 提供高分辨率的体内成像,但需要高剂量的辐射.
- 通过限制投射或光子流量来降低辐射剂量,引入噪音和人工物.
- 现有的深度学习方法需要高质量的参考数据,这在低剂量场景中往往是不可用的.
研究的目的:
- 为SR-CT开发一种新的低剂量成像策略,克服现有方法的局限性.
- 为了实现高质量的体内成像,减少辐射暴露.
- 创建一种不依赖于高质量的培训参考数据的方法.
主要方法:
- 介绍了Sparse2Noise,一种结合稀疏视图和全视图CT扫描数据的策略.
- 使用卷积神经网络 (CNN) 来进行图像重建和无声化.
- 在不需要高质量的重建数据的情况下训练模型,使用小数据集.
主要成果:
- Sparse2Noise有效地减少了噪音和环形工件,超过了最先进的无声化方法.
- 通过可接受的低辐射剂量 (0.5 Gy) 实现高图像质量,用于ex vivo老鼠后肢成像.
- 证明了在没有高质量的参考资料的情况下对小数据集进行培训的能力.
结论:
- Sparse2Noise代表了体内SR-CT成像技术的重大进步.
- 该方法允许在减少的辐射剂量下进行高质量的成像.
- Sparse2Noise适用于传统的CT和相对照CT消噪.
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