To analyze the classification procedure of identifying multiple sclerosis (MS) based on diffusion-weighted imaging data by using convolutional neural networks (CNNs), we generated relevance maps. The relevance maps indicate the contribution of each input voxel to the final classification score and may facilitate new findings regarding MS-specific biomarkers. The study showed that voxels in the central brain area including some of the lesion voxels are important for correct classification. This information may be used in the future to perform a more detailed analysis in order to classify different MS-phenotypes or predict disease progression.
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