Meeting Banner
Abstract #3283

IMPROVING THE CONTRAST OF CEREBRAL MICROBLEEDS ON T2*-WEIGHTED IMAGES USING DEEP LEARNING

Ozan Genc1, Sivakami Avadiappan1, Yicheng Chen2, Christopher Hess1, and Janine M. Lupo1
1Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 2Facebook Inc., Mountain View, CA, United States

This study trains a deep convolutional neural network to learn the SWI contrast from T2*-weighted magnitude images using a LSGAN deep learning model and assesses the performance of the resulting network on CMB detection. Our predicted SWI images were able to improve CMB contrast over T2* magnitude images and minimize residual artifacts from standard SWI processing.

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.

Keywords