Abstract #1961

Automatic 3D to 2D reformatting in 4D flow MRI using continuous reinforced learning

Javier Bisbal^1,2,3, Julio Sotelo^1,3,4, Cristobal Arrieta^1,3, Pablo Irarrázabal^1,2,3, Marcelo Andia^1,3,5, Cristian Tejos^1,2,3, and Sergio Uribe^1,3,5

¹Biomedical Imaging Center UC, Pontificia Universidad Catolica de Chile, Santiago, Chile, ²Electrical Engineering Department, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, ³ANID – Millennium Science Initiative Program – Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, ⁴School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso, Chile, ⁵Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile

Synopsis

One major limitation on 4D flow MRI is the time-consuming and user-dependent post-processing. We developed an automated reinforced deep learning framework for plane planning in 4D flow data. This method sequentially updates plane parameters towards a target plane based on a continuous policy. A total of 83 4D flow MRI scans were considered, 41 for training, 14 for validation and 28 for test. Our method achieves good results in terms of angulation and distance error (9.21 ± 3.85 degrees and 3.72 ± 2.19 mm).

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.