Multi-Contrast Reconstruction using Neural Network for Higher Acceleration

Clinical diagnosis requires several examinations to present various characteristics of organs, which are very time-consuming. To reduce total imaging time, many techniques have been proposed. Among them, parallel imaging techniques utilize sensitivity difference between multichannel RF coils. However, it is difficult to apply these techniques to higher acceleration due to SNR degradation. In this study, it is a key concept that each image in clinical protocols has different contrast, but shares similar structure information, and they are helpful for reconstructing each other. We propose a reconstruction model based on artificial neural network to allow to use higher acceleration factors.

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.