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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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基于深度学习的多次射击乳腺扩散MRI:改善成像质量和减少扭曲.

Ning Chien1, Yi-Hsuan Cho1, Ming-Yang Wang2

  • 1Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan.

European journal of radiology
|September 20, 2025
PubMed
概括

复杂灵敏编码的深度学习重建 (MUSE DL) 通过提高信号与噪声的比率和减少扭曲,显著提高了乳房MRI图像质量. 这种先进的技术保持了诊断准确度和明显扩散系数值,而不是标准的单次射击扩散加权成像.

关键词:
表面扩散系数的明显扩散系数乳房核磁共振成像深度学习重建的重建.扩散磁共振成像技术 扩散磁共振成像技术复杂感应编码 (MUSE) 是指多重感应编码.

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科学领域:

  • 放射学 放射学是指放射学
  • 医疗成像医学成像
  • 人工智能在医学中的应用

背景情况:

  • 一次射击扩散加权成像 (SS-DWI) 是乳腺MRI的标准技术.
  • 多重感应编码 (MUSE) 旨在通过在多个镜头中获取数据来提高图像质量.
  • 深度学习 (DL) 重建为进一步增强MRI技术提供了潜力.

研究的目的:

  • 为了比较深度学习重建的MUSE (MUSE DL) 与SS-DWI用于乳房MRI的成像性能.
  • 评估图像质量指标,包括信号噪声比 (SNR) 和图像扭曲.
  • 评估对明显扩散系数 (ADC) 值和诊断准确度的影响.

主要方法:

  • 一项前性研究,涉及61名女性参与者,65名女性患有乳腺病变.
  • 在3T核磁共振扫描仪上获取SS-DWI和多次射击MUSE DWI数据.
  • 对SNR,ADC值和豪斯多夫距离 (HD) 进行定量分析,以评估扭曲.
  • 使用利克尔特尺度进行主观定性分析.

主要成果:

  • 与非DL的MUSE相比,MUSE DL在纤维腺组织中显著改善了SNR (2次射击DL:207.8%,4次射击DL:175.1%).
  • 与SS-DWI (4.15毫米) 相比,观察到MUSE DL (2次拍摄:3.11毫米,4次拍摄:2.58毫米) 的图像扭曲明显减少.
  • 在良性或恶性瘤中,在MUSE,MUSE DL和SS-DWI之间没有发现ADC值的显著差异.

结论:

  • 通过改善SNR和最大限度地减少扭曲,MUSE DL提高了乳房MRI中的图像质量.
  • 该技术保持了病变特征和ADC值的诊断准确性.
  • MUSE DL代表了乳腺DWI的一个有希望的进步.