Meeting Banner
Abstract #0782

A Joint Multi-Scale Variational Neural Network for Accelerating Free-breathing Whole-Heart qBOOST-T2 mapping

Niccolo Fuin1, Giorgia Milotta1, Thomas Kuestner1, Aurelien Bustin1, Gastao Cruz1, Rene Botnar1,2, and Claudia Prieto1,2
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Pontificia Universidad Católica de Chile, Santiago, Chile

T2 mapping is a promising technique for the characterization of myocardial inflammation and oedema. We recently proposed a quantitative 3D whole-heart sequence (qBOOST-T2) which provides co-registered 3D high-resolution bright-blood and T2 map volumes from a single free-breathing scan. However, high-resolution qBOOST-T2 requires long scan times of ~10 min. Here we propose a joint Multi-Scale Variational Neural Network (jMS-VNN) to enable the acquisition of 3D high-resolution bright-blood and accurate T2 map volumes in ~3 mins, and their reconstruction in ~30s. The proposed jMS-VNN jointly reconstructs data from multiple contrasts and efficiently apply dictionary-based signal matching for fast T2 map generation.

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.

Keywords