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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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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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从MRI生成合成CT,使用基于3D变压器的消噪扩散模型.

Shaoyan Pan1,2, Elham Abouei1, Jacob Wynne1

  • 1Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.

Medical physics
|November 27, 2023
PubMed
概括

一个新的MRI-to-CT模型,MC-IDDPM,产生高质量的合成CT图像用于放射治疗规划. 这种基于变压器的扩散模型通过消除CT模拟的需要,减少了患者的辐射剂量和设置不确定性.

关键词:
这就是为什么MRI是MRI.深度学习是一种深度学习.扩散模型的扩散模型.合成CTCT 合成CT变压器变压器变压器变压器

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 辐射瘤学 辐射瘤学

背景情况:

  • 基于磁共振成像 (MRI) 的合成计算机断层扫描 (sCT) 简化了放射治疗的规划.
  • 消除CT模拟可以减少患者的辐射剂量和设置不确定性.

研究的目的:

  • 提出一个基于变压器的改进的消噪扩散概率模型 (MC-IDDPM) 进行MRI-to-CT转换.
  • 从MRI生成高质量的合成CT (sCT),以促进辐射治疗的规划.

主要方法:

  • 开发了使用扩散工艺和转移窗口变压器网络 (Swin-Vnet) 的MC-IDDPM.
  • 采用前向过程 (增加噪声) 和反向过程 (在MRI上条件化的消噪) 来生成sCT.
  • 评估了机构大脑和前列腺数据集的模型,使用定量指标 (MAE,PSNR,SSIM,NCC) 和剂量分析.

主要成果:

  • MC-IDDPM实现了对大脑sCT生成的最先进的定量结果.
  • 前列腺sCT生成也表现出MAE 55.124 ± 9.414 HU的强表现.
  • 与竞争网络相比,观察到具有统计学意义的改善 (p < 0.05),剂量测量差异在±0.34%内.

结论:

  • 开发并验证了一种基于变压器的新型DDPM,用于从MRI生成CT图像.
  • 该模型捕捉了复杂的CT-MRI关系,高效地产生高质量的sCT.
  • 这种方法可以简化放射治疗的规划,减少患者的时间,并提高治疗的准确性.