Automated segmentation of multiple sclerosis (MS) lesions in magnetic resonance imaging (MRI) has become central to both clinical research and routine care. Precise delineation of lesion load and ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, making it more applicable in clinical settings. The algorithm outperformed ...

A recent Npj Digital Medicine study assesses the accuracy and effectiveness of artificial intelligence (AI)-based imaging techniques to diagnose multiple sclerosis (MS). Study: A real-world clinical ...

Please provide your email address to receive an email when new articles are posted on . Ocrelizumab reduced the number and size of MS-related cortical lesions. Data synthesis featuring a mix of ...

"We plan to analyze these MRI structural measures longitudinally to determine if changes in brain volumes or lesion burden over time contribute to fatigue trajectories. More broadly, we might ...

Changes in NAWM and NAGM are crucial in MS progression, challenging the traditional lesion-centric model. Subtle alterations in myelin integrity, immune cell function, and neuronal connectivity ...

This study demonstrated progressive CP enlargement over time in individuals with RRMS, averaging 1.4% a year with significant variation per participant. CP enlargement correlated with the expansion of ...

White matter hyperintensities (WMHs) on fluid-attenuated inversion recovery (FLAIR) images are imaging features in various neurological diseases and essential markers for clinical impairment and ...

Two major health conditions appear to share a connection. Multiple sclerosis (MS), a disease which eats away at the body's central nervous system, affects millions of people globally and depression, a ...