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机器学习和深度学习在磁粒子成像中的应用

Saumya Nigam^1,2, Elvira Gjelaj^1,3, Rui Wang⁴

¹Precision Health Program, Michigan State University, East Lansing, Michigan, USA.

Journal of magnetic resonance imaging : JMRI

|February 15, 2024

概括

磁粒子成像 (MPI) 提供高灵敏度和分辨率. 本综述探讨了机器学习和深度学习如何增强MPI图像重建和分析,以便在未来取得进展.

科学领域:

医疗成像医学成像
生物物理学的生物物理.
人工智能的人工智能

背景情况:

磁粒子成像 (MPI) 是一种正在发展中的技术,提供高灵敏度和空间分辨率.
MPI提供2D/3D成像,具有高时间分辨率,非电离辐射和出色的对比度.
传统的MPI图像重建依赖于系统矩阵和X空间方法.

研究的目的:

审查机器学习 (ML) 和深度学习 (DL) 在MPI中的应用和意义.
突出人工智能驱动的方法提高MPI图像重建和分析的潜力.
总结MPI的AI当前的研究趋势.

主要方法:

对MPI中ML和DL应用的现有文献的审查.
对MPI信号处理和图像重建的基于AI的方法的分析.
讨论将AI整合到MPI工作流程中的问题.

主要成果:

人工智能,特别是ML和DL,在提高MPI图像质量和重建方面显示出重大前景.
这些方法可以解决传统MPI重建技术的局限性.
该审查确定了人工智能在MPI研究中产生影响的关键领域.

结论:

机器学习和深度学习对于推进磁粒子成像技术至关重要.
人工智能驱动的技术有望提高MPI的精度和实用性.
未来的研究应该专注于进一步开发和验证MPI应用的AI模型.

关键词:

人工智能的人工智能是人工智能.深度学习是一种深度学习.机器学习是机器学习.磁性颗粒成像技术磁性粒子成像技术

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