Abstract #1304

Attention-based convolutional network quantifying the importance of quantitative MR metrics in the multiple sclerosis lesion classification

Po-Jui Lu^1,2,3, Reza Rahmanzadeh^1,2, Riccardo Galbusera^1,2, Matthias Weigel^1,2,4, Youngjin Yoo³, Pascal Ceccaldi³, Yi Wang⁵, Jens Kuhle², Ludwig Kappos^1,2, Philippe Cattin⁶, Benjamin Odry⁷, Eli Gibson³, and Cristina Granziera^1,2

¹Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, ²Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland, ³Digital Technology and Innovation, Siemens Healthineers, Princeton, NJ, United States, ⁴Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland, ⁵Department of Radiology, Weill Cornell Medical College, New York, NY, United States, ⁶Center for medical Image Analysis & Navigation, Department of Biomedical Engineering, University of Basel, Basel, Switzerland, ⁷Covera Health, New York, NY, United States

White matter lesions in multiple sclerosis patients exhibit distinct characteristics depending on their locations in the brain. Multiple quantitative MR sequences sensitive to white matter micro-environment are necessary for the assessment of those lesions; but how to judge which sequences contain the most relevant information remains a challenge. In this abstract, we are proposing a convolutional neural network with a gated attention mechanism to quantify the importance of MR metrics in classifying juxtacortical and periventricular lesions. The results show the statistically significant order of quantitative importance of metrics, one step closer to combining more relevant metrics for better interpretation.

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.