5 papers
Efficient Transformer-Based Localized Patch Sampling for Choroid Plexus Segmentation in Multiple Sclerosis
Po-Jui Lu, Alessandro Cagol, Mario Ocampo-Pineda +12
Background: The lateral ventricle choroid plexus (LVCP) is gaining recognition as a key imaging biomarker for multiple sclerosis (MS) related to physical disability and neuroinflam…
Explaining Uncertainty in Multiple Sclerosis Cortical Lesion Segmentation Beyond Prediction Errors
Nataliia Molchanova, Pedro M. Gordaliza, Alessandro Cagol +14
Trustworthy artificial intelligence (AI) is essential in healthcare, particularly for high-stakes tasks like medical image segmentation. Explainable AI and uncertainty quantificati…
Instance-level quantitative saliency in multiple sclerosis lesion segmentation
Federico Spagnolo, Nataliia Molchanova, Meritxell Bach Cuadra +5
Explainable artificial intelligence (XAI) methods have been proposed to interpret model decisions in classification and, more recently, in semantic segmentation. However, instance-…
Benchmarking and Explaining Deep Learning Cortical Lesion MRI Segmentation in Multiple Sclerosis
Nataliia Molchanova, Alessandro Cagol, Mario Ocampo-Pineda +15
Cortical lesions (CLs) have emerged as valuable biomarkers in multiple sclerosis (MS), offering high diagnostic specificity and prognostic relevance. However, their routine clinica…
Unveiling Normative Trajectories of Lifespan Brain Maturation Using Quantitative MRI
Xinjie Chen, Mario Ocampo-Pineda, Po-Jui Lu +17
Background: Brain maturation and aging involve significant microstructural changes, resulting in functional and cognitive alterations. Quantitative MRI (qMRI) can measure this evol…