Abstract #2734

Automatic Myocardium Segmentation using Fully Conventional Network (FCN)

Yan Wang¹, Peng Cao¹, Karen Ordovas¹, and Jing Liu¹

¹University of California, San Francisco, San Francisco, CA, United States

We introduce a new methodology that combines deep learning and level set for the automated segmentation of the myocardium from cardiac cine magnetic resonance (MR) data. The method employs deep learning algorithm to learn the segmentation task from the ground truth data. The inferred shape is incorporated into level set model to improve the accuracy and robustness of the segmentation.

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.