Magnetic resonance (MR) imaging plays a pivotal role in the staging and treatment planning of rectal cancer. Accurate staging depends on good-quality high-resolution axial T2-weighted images orthogonal to the rectal tumor. Rectal MRI is often confounded by motion artifacts secondary to bowel peristalsis and patient movement. We propose a CNN model that automatically assesses image quality instantaneously after a scan is finished to reduce the frequency of patient recalls and non-diagnostic images. Our model achieves high accuracy in identifying motion degradation on an individual slice basis and perfect accuracy when classifying the entire sequence.
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