Abstract #2232

Deep learning-based tumor segmentation from postoperative MRI

Jingpeng Li^1,2, Jonas Vardal^3,4, Inge Groote¹, and Atle Bjornerud^1,2

¹Computational Radiology and Artificial Intelligence, Oslo University Hospital, Oslo, Norway, ²Department of Physics, University of Oslo, Oslo, Norway, ³The Intervention Centre, Oslo University Hospital, Oslo, Norway, ⁴Faculty of Medicine, University of Oslo, Oslo, Norway

Synopsis

To accurately detect and localize postoperative tumor after surgery is of critical importance to postoperative patient management and survial rate. We propose a fully automated end-to-end coarse-to-fine segmentation approach for the segmentation of posoperative tumor.

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.