Abstract #5135

The Value of Deep Learning Reconstruction In Improving the Image Quality of rectum MRI Images

Sijie Hu¹, Yueluan Jiang², and Nickel Marcel Dominik³

¹Department of Diagnostic Radiology, National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, ²MR Research Collaboration, Siemens Healthineers, Beijing, China, ³MR Application Predevelopment,, Siemens Healthineers AG, Erlangen, Germany

Synopsis

Keywords:

Motivation: TSE sequences are crucial for rectum MRI, but have limitations. DL-TSE is expected to improve image quality and reduce acquisition time for rectum MRI.

Goal(s): To assess the viability of employing TSE sequences with deep learning reconstruction for rectal MRI when compared to conventional TSE sequences.

Approach: This study included 16 patients with colorectal cancer confirmed by pathology. SNR and CNR were analyzed by SPSS 22.0 software.A P-value below 0.05 was considered statistically significant.

Results: The results show that the application of deep learning can shorten the scanning time while maintaining high image resolution, and improve the diagnostic efficiency of rectal diseases.

Impact: Deep learning reconstruction of TSE sequence in rectal MRI has the advantages of shortening acquisition time, improving image quality, and improving diagnostic efficiency. DL-TSE may also be extended to MRI examinations of other organs, such as the prostate and pelvis.

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