Leveraging Temporal Differences for Improved Longitudinal Segmentation of Multiple Sclerosis Lesions

Incorporating explicit architectural bias to emphasize temporal differences between baseline and follow-up scans significantly enhances the performance of longitudinal multiple sclerosis lesion segmentation compared to state-of-the-art single timepoint and existing longitudinal methods.