XLSTM-HVED combines a heteromodal variational encoder-decoder with Vision XLSTM and attention-based fusion to improve brain tumor segmentation under missing MRI modalities, reporting state-of-the-art Dice and HD95 on BraTS 2024.
Our model enhances segmentation accuracy and MRI data reconstruction quality by integrating cross-modal encoding, multi-task learning, and attention mechanisms
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XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder
XLSTM-HVED combines a heteromodal variational encoder-decoder with Vision XLSTM and attention-based fusion to improve brain tumor segmentation under missing MRI modalities, reporting state-of-the-art Dice and HD95 on BraTS 2024.