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Found 3 papers, 3 papers with code
Synthetic Data for Robust Stroke Segmentation
Deep learning-based semantic segmentation in neuroimaging currently requires high-resolution scans and extensive annotated datasets, posing significant barriers to clinical applicability.
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge.
Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation
Vision transformers are effective deep learning models for vision tasks, including medical image segmentation.
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