3 papers
eess.IV2026
Optimization in Sparse 2D to Dense 3D Weakly Supervised Learning: Application to Multi-Label Segmentation of Large ex vivo MRI Data
Paul Hoareau, Kuan Yi Wang, Brandon Bujak +6
INTRODUCTION | Fully supervised 3D segmentation of high-resolution ex vivo MRI is limited by the prohibitive cost of volumetric annotation, forcing reliance on sparse 2D slices. We…
cs.CV2025
Monitoring morphometric drift in lifelong learning segmentation of the spinal cord
Enamundram Naga Karthik, Sandrine Bédard, Jan Valošek +53
Morphometric measures derived from spinal cord segmentations can serve as diagnostic and prognostic biomarkers in neurological diseases and injuries affecting the spinal cord. Whil…
eess.IV2025
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…