Deep learning has shown encouraging performance for lesion detection, but it is limited due to the high requirement of data labeling. In the task of lumbar intervertebral disc herniation recognition, we proposed to develop a recognition method based on axial images, which include more anatomical information about the disc, using a convolutional network. And we attempt to provide possible pathological evidence from the weakly labeled training data (normal/herniated label on image level).
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