Meeting Banner
Abstract #2804

Automatic Segmentation of Diffusely Abnormal White Matter in MS Using Deep Neural Network

Refaat E Gabr1 and Ponnada A Narayana1
1Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, TX, United States

Deep neural network was used to automatically segment diffusely abnormal white matter (DAWM) in 100 relapsing remitting multiple sclerosis patients (RRMS). Our calculated DAWM prevalence of 32% is comparable to ~ 25% reported elsewhere. Based on our studies, only 13% of T2 lesions at baseline converted into DAWM by 60 months. Of the DAWM detected at baseline, only 15% converted to lesions, 45% persisted, and 40% resolved (converted to NAWM). These initial results suggest that DAWM may present a significant disease burden by itself.

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