most citedInstance-level quantitative saliency in multiple sclerosis lesion segmentation

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

physics.med-ph2024★ 2 cited

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…

eess.IV2024

Exploiting XAI maps to improve MS lesion segmentation and detection in MRI

Federico Spagnolo, Nataliia Molchanova, Mario Ocampo Pineda +5

To date, several methods have been developed to explain deep learning algorithms for classification tasks. Recently, an adaptation of two of such methods has been proposed to gener…

eess.IV2024★ 3 cited

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-…

eess.IV2024★ 1 cited

Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting

Alicia Durrer, Julia Wolleb, Florentin Bieder +12

Monitoring diseases that affect the brain's structural integrity requires automated analysis of magnetic resonance (MR) images, e.g., for the evaluation of volumetric changes. Howe…