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Abstract Stroke lesion segmentation plays a critical role in clinical diagnosis, prognosis and rehabilitation treatment. However, this task remains highly challenging due to inter-subject differences, shape variations, noise and artifacts in MR images, which hinder the accurate extraction of stroke regions. This work proposes a novel hybrid framework for accurate stroke lesion segmentation from MR images termed HFFS-net.
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