It is essential to segment right
ventricle (RV) for evaluating cardiac functional parameters of cardiac diseases
in clinical diagnosis and prognosis. However, the complex structure of RV makes
traditional segmentation methods not so effective in right ventricular
segmentation. A new Dense and Multi-scale U-net deep learning method is
proposed to segment right ventricle in cine cardiac magnetic resonance (CMR) short-axis
images automatically, which shows high coincidence and small difference with
manual segmentation and is promising for diagnosis and analysis of clinical
cardiac diseases.
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.
Keywords