Keywords: Multiple Sclerosis, NeuroinflammationThalamic atrophy has been found since the earliest phases of multiple sclerosis (MS). However, this measure is not included in clinical practice, due to the time-consuming manual segmentation and technical challenges. By comparing thalamic segmentations from three available automatic methods in a multicenter dataset, we found that the inclusion of fractional anisotropy maps facilitated the automatic identification of thalamic boundaries increasing robustness of the results. In particular, the multimodal approach (FSL-MIST) showed a better capability to detect small longitudinal variations of thalamic volumes in MS patients and a better correlation with another relevant MRI measure such as the lesion volume.
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