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Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter‐rater reliability. To accelerate this task, we developed a deep‐learning‐based framework (CLAIMS: Cortical Lesion AI‐Based Assessment in Multiple Sclerosis) for the automated detection and classification of MS CLs with 7 T MRI. Two 7 T datasets, acquired at...
The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter‐rater variability and the expenditure of time associated with manual assessment. We describe a deep learning‐based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We...
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