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Texas A&M University, College Station, TX, USA
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MambaLiteUNet achieves state-of-the-art skin lesion segmentation with 93% fewer parameters and 97% fewer GFLOPs than U-Net, proving that efficient architectures can outperform traditional models in medical imaging.
