LSU-Net combines depthwise separable convolutions, a spatial shift block, and adaptive multi-level loss to achieve strong organ segmentation with 1.08M parameters.
Deep learning has significantly advanced the field with diverse network ar- chitectures, especially the U-shaped encoder-decoder design starting with UNet [1]
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LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images
LSU-Net combines depthwise separable convolutions, a spatial shift block, and adaptive multi-level loss to achieve strong organ segmentation with 1.08M parameters.