Jiahong Ouyang1, kevin Chen2, and Greg Zaharchuk2
1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Department of Radiology, Stanford University, Stanford, CA, United States
1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Department of Radiology, Stanford University, Stanford, CA, United States
We synthesized high-quality FDG-PET brain images from multi-contrast MR images by a U-Net based network with attention modules. We demonstrated better performance to create FDG PET, broadening the potential value of MR to provide molecular imaging information without the use of radiation.
Figure 2. Qualitative Results of two representative slices. (a) Input MR images, ground truth PET images, and the
synthesized PET images by three methods. (b) Spatial attention map from Attention U-Net and the proposed method.
Figure 1. Overview of the proposed method.
