LightMIS: Ultra-Lightweight Medical Image Segmentation Without a Stage-Wise Decoder

arXiv:2609.28327 · cs.CV · Submitted 2026-09-23 · Read on arXiv

cs.CV

Submitted: 2026-09-23

Updated: 2026-09-24

Code: https://github.com/AndreiiArhire/LightMIS

Terminology

• nnU-Net — 47× in this paper · explained in 2 episodes
• Transformer — 19× in this paper · explained in 2 episodes
• Aggregation — 17× in this paper · explained in 1 episode
• Ablation — 7× in this paper · explained in 1 episode
• Accuracy — 7× in this paper · explained in 1 episode
• Progressive Receptive Fusion — 7× in this paper
• Benchmark — 6× in this paper · explained in 2 episodes
• Scale-Aligned Projection — 6× in this paper
• Adaptive Fusion Cascade — 5× in this paper
• Adaptive Kernel Fusion — 5× in this paper
• Computer Vision and Pattern Recognition — 5× in this paper
• Benchmarking — 4× in this paper · explained in 3 episodes
• International Symposium on Biomedical Imaging — 4× in this paper
• Alignment — 3× in this paper · explained in 1 episode
• Medical Image Computing and Computer Assisted Intervention — 3× in this paper
• U-net architecture — 3× in this paper · explained in 3 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Average Symmetric Surface Distance — 1× in this paper
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Edge Deployment — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Semantic Gap — 1× in this paper · explained in 2 episodes

Sources

• Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
• Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture
• U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation
• Attention U-Net: Learning Where to Look for the Pancreas

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