We propose an anatomical convolutional module to couple anatomical information into deep neural network. We further develop a loss function based on the mass center of individual lesions called lesion-wise loss, which can regularize the network training, thereby improving the performance of lesion localization and segmentation. We validate our methods on a public dataset, ISBI-15 Multiple Sclerosis Lesion Segmentation Challenge [1], where the results showed that we achieved the best performance on all published methods.
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