We developed a 3D convolutional neural network for the automatic segmentation of the thoracic aorta in 4D Flow-derived 3D PC-MRAs. Using 100 testing datasets, we obtained an average dice score of 0.94±0.03 and an average voxel-wise accuracy of 0.99. Additionally, our algorithm is robust enough to accurately segment a wide array of aortic geometries and disease, such as bicuspid aortic value, coarctation, and interrupted aortic arches.
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