使GABA

Hanna Bugler1, Rodrigo Berto1, Roberto Souza2

  • 1Department of Biomedical Engineering, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada.

PubMed
概括

复杂值输入和卷积显著改善卷积神经网络 (CNN) 在GABA编辑磁共振光谱 (MRS) 数据中的频率和相位校正 (FPC) 性能,优于现有的深度学习模型.