Multi‐parametric MRI synthesis for glioblastoma from quantitative MR fingerprinting: Quantitative synthetic neural network (QS‐Net)

Key Points

• This research aims to develop a deep learning model called QS-Net for synthesizing multi-parametric MRI (mpMRI) images from quantitative MR fingerprinting (MRF) maps.
• Developed QS-Net, a deep learning model.
• Utilized quantitative MRF maps as input data.
• Compared results against conventional qualitative MRI approaches.
• QS-Net demonstrated superior image synthesis quality.
• Achieved better cross-vendor generalization than traditional methods.

Abstract