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探索物理信息神经网络的潜力,以在扩散存在的情况下从DCE-MRI中提取血管化数据

D Sainz-DeMena1, M A Pérez1, J M García-Aznar1

  • 1Department of Mechanical Engineering, Aragon Institute for Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain.

Medical engineering & physics
|February 16, 2024
PubMed
概括

基于物理学的神经网络 (PINNs) 通过结合对比剂扩散来改善动态对比增强MRI (DCE-MRI) 分析. 这种新的方法提高了组织血管化评估的准确性,特别是在复杂的瘤环境中.

关键词:
在DCE-MRI中,使用的是DCE-MRI.扩展的Tofts模型模型反向问题是反向的问题.基于物理学的神经网络.

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