Advanced MRI Lesion Segmentation
Leveraging AI to enhance diagnosis and monitoring of Multiple Sclerosis through precise lesion mapping.
MS Lesion Segmentation
An advanced AI pipeline for automated segmentation of multiple sclerosis lesions in FLAIR MRI scans. Our system leverages a Bayesian Mamba-adapted EfficientNet to address extreme class imbalance, providing precise segmentation of periventricular, juxtacortical, and infratentorial lesions with uncertainty quantification to support clinical decision-making. Built on our “Brain MRI Dataset of Multiple Sclerosis,” the pipeline tackles lesion sparsity and anatomical variability for improved diagnostic accuracy.
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Hybrid Encoder
Combines pretrained EfficientNet (ImageNet) with Mamba adapters after each block to capture volumetric context in MRI scans.
Bayesian Model
Employs probabilistic convolution with variational inference to provide uncertainty maps for clinical trust.
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