:""fMRI.

Frank Riemer1, Marius Eldevik Rusaas2, Lydia Brunvoll Sandøy2

  • 1Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, 5021, Bergen, Norway; Neuro-SysMed, Department of Neurology, Haukeland University Hospital, 5021, Bergen, Norway; Department of Physics and Technology, University of Bergen, 5007, Bergen, Norway.

概括

深度学习图像增强提高了静音功能性MRI (fMRI) 的质量. 一个3D-UNet模型显著减少了错误和保留了时间信号变化,使其适合噪声敏感的fMRI研究.