Keywords: Machine Learning/Artificial Intelligence, Image Reconstruction, rectum; magnetic resonance imaging; T2-weighted imaging
High-resolution MRI is of much significance in preoperatively staging rectal cancer. However, the motion artifact from intestinal peristalsis inevitably affects image quality then the accuracy of staging. Deep learning reconstruction (DLRecon) that uses artificial neural networks to extract patterns and makes predictions from large data sets, has been verified in related studies for improving image quality and reducing scanning time. In this study, rectum T2-weighted imaging (T2WI) reconstructed with DLRecon and conventional reconstruction were evaluated, and the results indicate that DLRecon could be employed for better image quality without extra scanning time in clinical practice.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords