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多频时间依赖深度图像 在实时自由呼吸心脏成像之前.

Jesse I Hamilton1,2, Gastao Cruz1, William Truesdell1

  • 1Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.

NMR in biomedicine
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概括

一种新的多频时间DIP方法可以实现高分辨率,实时的心脏MRI,无需屏息或心电图门. 这一进步改善了心律失常患者的成像,在自由呼吸扫描中提供了更好的运动器件减少和图像质量.

关键词:
心脏成像 - - 心脏成像深度学习是一种深度学习.多样化的多元化.非卡特西安的非卡特西安.实时实时的时间.

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科学领域:

  • 医疗成像医学成像
  • 心血管核磁共振 (MRI) 是一种心血管核磁共振.
  • 人工智能在医学中的应用

背景情况:

  • 实时心脏MRI对于评估心脏功能至关重要,特别是在无法屏住呼吸或心律失常的患者中.
  • 现有的时间依赖深度图像先验 (Time-DIP) 方法虽然有希望,但依赖于不适合自由呼吸扫描的运动周期性假设.
  • 当前实时心脏MRI的局限性阻碍了对具有挑战性的患者群体的准确评估.

研究的目的:

  • 开发和验证一种新的多频时间DIP技术,用于高时间分辨率,自由呼吸的心脏MRI.
  • 为了克服以前用于实时成像的时间-DIP方法的运动周期性限制.
  • 为了能够在患有心律失常的患者中使用自由呼吸MRI进行强有力的心脏功能评估.

主要方法:

  • 引入了一种"多频分组"来参数化时间,而不需要假设运动周期性.
  • 通过零射击深度学习对线圈灵敏度的联合估计,以改进多道数据重建.
  • 验证了多频时间DIP技术使用模拟和2D自由呼吸无螺旋bSSFP序列在健康受试者和患者,包括那些心律不整.

主要成果:

  • 与其他实时技术相比,多频时间DIP在模拟中表现出优异的性能.
  • 在体内扫描显示了减少的别名器件,并实现了高时间分辨率 (4.2 ms/frame).
  • 左心室 (LV) 功能测量与传统扫描相比,在实时方法中改善了图像质量指标.

结论:

  • 一般化的多频时间-DIP重建成功实现了高时间分辨率,自由呼吸的实时心脏成像.
  • 这种方法在健康个体和患者中都有效,包括心律不整的人.
  • 多频时间DIP代表了动态心脏MRI在具有挑战性的临床场景中的重大进步.