Keywords: Machine Learning/Artificial Intelligence, Magnetization transfer, Multi-ModalThis study presents an evaluation of utilizing MTR and FLAIR as compared to T1wCE and FLAIR images for automatic segmentation of brain metastases, due to the unknown consequences posed by accumulated contrast enhancement. Numerous combinations of FLAIR, T1wCE, and MTR MRI images were tested on three top-performing segmentation models (MS-FCN, U-NET, and SegresNet) to evaluate the feasibility of using MTR and FLAIR images for tumor segmentation. Overall, the U-Net produced the best similarity scores of 0.4±0.15 using MTR and FLAIR images. A future study will test the utility of 3D MTR images for tumor segmentation using convolutional and full-connected models.
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