Abstract #0240

Comparing neural networks for synthesizing FLAIR images from T1WI and T2WI

Takashi Abe¹, Yuki Matsumoto¹, Yuki Kanazawa¹, Yoichi Otomi¹, Maki Otomo¹, Moriaki Yamanaka¹, Mihoko Kondo¹, Saya Matsuzaki¹, Ariunbold Gankhuyag¹, Enkhamgalan Dolgorsuren ¹, Oyundari Gonchigsuren¹, and Masafumi Harada¹

¹Graduate School of Biomedical Sciences, Tokushima University, Tokushima, Japan

We checked the performances of different convolutional encoder decoder (CED), one of the neural networks when synthesizing FLAIR using T1WI and T2WI. With the shallow CED, the resolution was good but the contrast was poor, and when the CED became deeper, contrast became better, but the resolution became worse. Next we also added “skip-connection” to CED, but the image quality was not improved with the Inception(GoogLeNet)-like parallel skip-connection, and the image quality improved with the ResNet-like serial skip-connection; that was a mixture of shallow and deep CED, and resembled the structure of U-net.

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.