Abstract #2654

Deep learning fat-suppressed images for musculoskeletal diseases

Shimpei Kato^1,2, Akihiko Wada¹, Yuya Saito^1,3, Christina Andica¹, Shohei Fujita^1,2, Kotaro Fujimoto^1,2, Yutaka Ikenouchi¹, Akifumi Hagiwara¹, Junko Kikuta⁴, Kanako Sato^1,2, Michimasa Suzuki¹, Toshiaki Akashi¹, Maki Amano¹, Koji Kamagata¹, Kanako Kumamaru^1,2, Masaaki Hori^1,5, Atsushi Nakanishi¹, Osamu Abe², and Shigeki Aoki¹

¹Department of Radiology, Juntendo University, Tokyo, Japan, ²Department of Radiology, The University of Tokyo, Tokyo, Japan, ³Faculty of Health Sciences Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan, ⁴Department of Radiology, Juntendo University Nerima Hospital, Tokyo, Japan, ⁵Department of Radiology, Toho University, Tokyo, Japan

Fat-suppressed MR images of the musculoskeletal system help the visualization of T2-prolonged lesions, such as tumors, infections/inflammations, and trauma, with better contrast, while also contributing to the qualitative diagnosis of fatty lesions.However, the addition of a fat-suppressing sequence to clinical routine is time-consuming. Increasing the imaging time may lead to deterioration of the image quality due to body movement.In this study, we generated fat-suppressed images through post-processing by using deep learning. The images were generated using U-Net, with T1WIs and T2WIs as input. The generated images were very similar to Dixon images that were used as targets.

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.

Click here for more information on becoming a member.