Abstract #0030

Using convolutional neural networks to predict infarct development in acute ischemic stroke patients: does reperfusion status matter?

Yuan Xie¹, Yannan Yu¹, Thoralf Thamm¹, Charles Huang¹, Enhao Gong¹, Soren Christensen¹, Maarten Lansberg¹, and Greg Zaharchuk¹

¹Stanford University, Stanford, CA, United States

Convolutional Neural Network has shown promising results in stroke treatment outcome predictions. Our study explores the hypothesis of whether training a CNN model with patients who have similar treatment outcomes can improve the model prediction of day 5 stroke lesion.

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.