Abstract #3148

Deep Learning Reconstruction for Abdomen Diagnosis: Improvement of Diagnostic Performance with higher Spatial or Temporal Resolution

Bo-Ting Chen^1,2, Cheng-Ya Yeh², Yi-Chen Chen², Chia-Wei Li³, Charng-Chyi Shieh³, Chien-Yuan Lin³, and Kao-Lang Liu^1,2

¹Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan, ²Department of Medical Imaging, National Taiwan University Cancer Center and National Taiwan University College of Medicine, Taipei, Taiwan, ³GE Healthcare, Taipei, Taiwan

Synopsis

Keywords: Liver, Machine Learning/Artificial Intelligence, Deep learning reconstruction, Abdomen diagnosisWe have previously validated the SNR improvement of abdominal MRI by Deep Learning Reconstruction (DLRecon). In this study, we further investigate the improvement of image quality and diagnostic performance when trading the SNR with higher spatial and temporal resolution imaging setting. In the result, the clinical scoring of images with high-speed or high-resolution settings in DLRecon was superior to that of the images with conventional setting and reconstruction.

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