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Magnetic Resonance Imaging01:24

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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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变形编码深度学习变压器用于高率心脏影像MRI.

Manuel A Morales1, Fahime Ghanbari1, Shiro Nakamori1

  • 1From the Cardiovascular Medicine Division, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave, Boston, MA 02215 (M.A.M., F.G., S.N., S.A., A.A., S.Y., J.R., R.N.); Division of Cardiology, Department of Medicine, Tufts Medical Center, Boston, Mass (M.S.M., E.J.R.); Division of Cardiology, Weill Cornell Medicine, New York, NY (J.K., J.W.W.); and Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC (R.M.J.).

Radiology. Cardiothoracic imaging
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PubMed
概括

一个新的深度学习模型可以提高心脏电影率,而不会牺牲图像质量或扫描时间. 这种基于变压器的方法产生了与实际高率相似的图像,改善了心脏MRI诊断.

关键词:
一个心脏病患者的心脏病.深度学习 (Deep Learning) 是一种深度学习.功能性核磁共振成像 (MRI) 是一种功能性核磁共振成像.心灵的心脏心脏的心脏心脏心脏高率的高率.

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科学领域:

  • 心血管成像 - 心血管成像
  • 人工智能在医学中的应用
  • 医疗图像处理 医学图像处理

背景情况:

  • 心脏MRI (cMRI) 对于心脏评估至关重要.
  • 增加心脏电影MRI的率可以提高时间分辨率,但可以延长扫描时间或减少空间分辨率.
  • 深度学习为增强图像采集参数提供了潜在的解决方案.

研究的目的:

  • 开发和验证基于变压器的深度学习模型,以增加心脏电影MRI率.
  • 保持空间分辨率和扫描时间,同时改善时间信息.
  • 将模型的性能与传统的插值方法进行比较.

主要方法:

  • 基于变压器的深度学习模型在来自多个中心和供应商的大量回顾性数据集 (5840名患者) 上受训.
  • 该模型的插值性能使用根平均平方误差 (RMSE) 与线性和双立方方法进行了评估.
  • 一项前性研究评估了读者在实际和模型间调整的高率 (50 fps) 电影之间的偏好.

主要成果:

  • 深度学习模型生成了无工件的插入心脏影像图像.
  • 在内部和外部测试中,基于模型的插值显示RMSE与线性和双立方方法相比显著较低.
  • 读者研究表明非劣等性,大多数读者在实际和插入的50fps电影之间"没有偏好".

结论:

  • 一个基于变压器的深度学习模型有效地增加了心脏电影率.
  • 开发的模型保留了空间分辨率和扫描时间,产生与实际高率相似的图像质量.
  • 这种深度学习方法有望提高心脏MRI诊断能力.