LBMNet: a hybrid multi-scale CNN–Mamba framework for enhanced 3D stroke lesion segmentation in MRI

Extensive experiments on two benchmark datasets demonstrate state-of-the-art performance, achieving Dice coefficients of 67.57% on ATLAS v2.0 and 82.03% on ISLES 2022. Compared with existing CNN, Transformer, and hybrid models, LBMNet shows significant improvements in small lesion segmentation. This study presents a robust and efficient framework with strong clinical potential for accurate stroke lesion segmentation across diverse lesion sizes and morphologies.