联合频率图像域网用于磁粒子成像中的图像恢复
Haoran Zhang1, Bo Zhang1, Gen Shi1
1School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People's Republic of China.
Physics in medicine and biology
|October 13, 2025
概括
磁粒子成像 (MPI) 来自视野之外的信号的边界工件使用一种新的双域网络来减少. 这个JFI-Net增强了图像恢复,以实现MPI技术的准确临床翻译.
科学领域:
- 医疗成像医学成像
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 磁粒子成像 (MPI) 是一个有前途的临床前成像技术.
- 在视野 (FOV) 外的超偏磁铁氧化物纳米粒子 (SPIO) 导致边界工件,影响MPI图像的准确性.
- 现有的人工物减少方法需要改进,以便实时临床应用.
研究的目的:
- 开发一个准确的MPI图像恢复方法来克服边界文物.
- 通过提高定量准确性来提高MPI技术的临床翻译.
主要方法:
- 探索了FOV内部和外部的SPIO信号之间的光谱差异.
- 设计了一个双域联合学习网络 (JFI-Net),使用受影响的图像和时间频率图.
- 实现特征提取和自适应加权融合,以增强图像恢复.
主要成果:
- 拟议的JFI-Net在OpenMPI和模拟数据集上表现优于现有的方法.
- 将JFI-Net应用于内部手持MPI系统,提高大型船舶幻影的成像准确性.
- 废弃性研究证实了JFI-Net的特征提取和融合模块的有效性.
结论:
- JFI-Net为MPI图像恢复提供了创新和高效的解决方案,显著提高了定量准确性.
- 这种方法解决了边界工件,为MPI技术的更广泛的临床应用铺平了道路.
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